WorldWideScience

Sample records for video text extraction

  1. Fuzzy-Based Segmentation for Variable Font-Sized Text Extraction from Images/Videos

    Directory of Open Access Journals (Sweden)

    Samabia Tehsin

    2014-01-01

    Full Text Available Textual information embedded in multimedia can provide a vital tool for indexing and retrieval. A lot of work is done in the field of text localization and detection because of its very fundamental importance. One of the biggest challenges of text detection is to deal with variation in font sizes and image resolution. This problem gets elevated due to the undersegmentation or oversegmentation of the regions in an image. The paper addresses this problem by proposing a solution using novel fuzzy-based method. This paper advocates postprocessing segmentation method that can solve the problem of variation in text sizes and image resolution. The methodology is tested on ICDAR 2011 Robust Reading Challenge dataset which amply proves the strength of the recommended method.

  2. VideoSET: Video Summary Evaluation through Text

    OpenAIRE

    Yeung, Serena; Fathi, Alireza; Fei-Fei, Li

    2014-01-01

    In this paper we present VideoSET, a method for Video Summary Evaluation through Text that can evaluate how well a video summary is able to retain the semantic information contained in its original video. We observe that semantics is most easily expressed in words, and develop a text-based approach for the evaluation. Given a video summary, a text representation of the video summary is first generated, and an NLP-based metric is then used to measure its semantic distance to ground-truth text ...

  3. Linking Video and Text via Representations of Narrative

    OpenAIRE

    Salway, Andrew; Graham, Mike; Tomadaki, Eleftheria; Xu, Yan

    2003-01-01

    The ongoing TIWO project is investigating the synthesis of language technologies, like information extraction and corpus-based text analysis, video data modeling and knowledge representation. The aim is to develop a computational account of how video and text can be integrated by representations of narrative in multimedia systems. The multimedia domain is that of film and audio description – an emerging text type that is produced specifically to be informative about the events and objects dep...

  4. Identifying sports videos using replay, text, and camera motion features

    Science.gov (United States)

    Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

    1999-12-01

    Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

  5. Intelligent keyframe extraction for video printing

    Science.gov (United States)

    Zhang, Tong

    2004-10-01

    Nowadays most digital cameras have the functionality of taking short video clips, with the length of video ranging from several seconds to a couple of minutes. The purpose of this research is to develop an algorithm which extracts an optimal set of keyframes from each short video clip so that the user could obtain proper video frames to print out. In current video printing systems, keyframes are normally obtained by evenly sampling the video clip over time. Such an approach, however, may not reflect highlights or regions of interest in the video. Keyframes derived in this way may also be improper for video printing in terms of either content or image quality. In this paper, we present an intelligent keyframe extraction approach to derive an improved keyframe set by performing semantic analysis of the video content. For a video clip, a number of video and audio features are analyzed to first generate a candidate keyframe set. These features include accumulative color histogram and color layout differences, camera motion estimation, moving object tracking, face detection and audio event detection. Then, the candidate keyframes are clustered and evaluated to obtain a final keyframe set. The objective is to automatically generate a limited number of keyframes to show different views of the scene; to show different people and their actions in the scene; and to tell the story in the video shot. Moreover, frame extraction for video printing, which is a rather subjective problem, is considered in this work for the first time, and a semi-automatic approach is proposed.

  6. Figure text extraction in biomedical literature.

    Directory of Open Access Journals (Sweden)

    Daehyun Kim

    2011-01-01

    Full Text Available Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures.We first evaluated an off-the-shelf Optical Character Recognition (OCR tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons.The evaluation on 382 figures (9,643 figure texts in total randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36.6% precision, 19.3% recall, and 25.3% F1-score for

  7. Bengali text summarization by sentence extraction

    OpenAIRE

    Sarkar, Kamal

    2012-01-01

    Text summarization is a process to produce an abstract or a summary by selecting significant portion of the information from one or more texts. In an automatic text summarization process, a text is given to the computer and the computer returns a shorter less redundant extract or abstract of the original text(s). Many techniques have been developed for summarizing English text(s). But, a very few attempts have been made for Bengali text summarization. This paper presents a method for Bengali ...

  8. Ontology Assisted Formal Specification Extraction from Text

    Directory of Open Access Journals (Sweden)

    Andreea Mihis

    2010-12-01

    Full Text Available In the field of knowledge processing, the ontologies are the most important mean. They make possible for the computer to understand better the natural language and to make judgments. In this paper, a method which use ontologies in the semi-automatic extraction of formal specifications from a natural language text is proposed.

  9. Unsupervised information extraction by text segmentation

    CERN Document Server

    Cortez, Eli

    2013-01-01

    A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors' approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a

  10. Bollywood Movie Corpus for Text, Images and Videos

    OpenAIRE

    Madaan, Nishtha; Mehta, Sameep; Saxena, Mayank; Aggarwal, Aditi; Agrawaal, Taneea S; Malhotra, Vrinda

    2017-01-01

    In past few years, several data-sets have been released for text and images. We present an approach to create the data-set for use in detecting and removing gender bias from text. We also include a set of challenges we have faced while creating this corpora. In this work, we have worked with movie data from Wikipedia plots and movie trailers from YouTube. Our Bollywood Movie corpus contains 4000 movies extracted from Wikipedia and 880 trailers extracted from YouTube which were released from 1...

  11. Terminology extraction from medical texts in Polish.

    Science.gov (United States)

    Marciniak, Małgorzata; Mykowiecka, Agnieszka

    2014-01-01

    Hospital documents contain free text describing the most important facts relating to patients and their illnesses. These documents are written in specific language containing medical terminology related to hospital treatment. Their automatic processing can help in verifying the consistency of hospital documentation and obtaining statistical data. To perform this task we need information on the phrases we are looking for. At the moment, clinical Polish resources are sparse. The existing terminologies, such as Polish Medical Subject Headings (MeSH), do not provide sufficient coverage for clinical tasks. It would be helpful therefore if it were possible to automatically prepare, on the basis of a data sample, an initial set of terms which, after manual verification, could be used for the purpose of information extraction. Using a combination of linguistic and statistical methods for processing over 1200 children hospital discharge records, we obtained a list of single and multiword terms used in hospital discharge documents written in Polish. The phrases are ordered according to their presumed importance in domain texts measured by the frequency of use of a phrase and the variety of its contexts. The evaluation showed that the automatically identified phrases cover about 84% of terms in domain texts. At the top of the ranked list, only 4% out of 400 terms were incorrect while out of the final 200, 20% of expressions were either not domain related or syntactically incorrect. We also observed that 70% of the obtained terms are not included in the Polish MeSH. Automatic terminology extraction can give results which are of a quality high enough to be taken as a starting point for building domain related terminological dictionaries or ontologies. This approach can be useful for preparing terminological resources for very specific subdomains for which no relevant terminologies already exist. The evaluation performed showed that none of the tested ranking procedures were

  12. Advanced text and video analytics for proactive decision making

    Science.gov (United States)

    Bowman, Elizabeth K.; Turek, Matt; Tunison, Paul; Porter, Reed; Thomas, Steve; Gintautas, Vadas; Shargo, Peter; Lin, Jessica; Li, Qingzhe; Gao, Yifeng; Li, Xiaosheng; Mittu, Ranjeev; Rosé, Carolyn Penstein; Maki, Keith; Bogart, Chris; Choudhari, Samrihdi Shree

    2017-05-01

    Today's warfighters operate in a highly dynamic and uncertain world, and face many competing demands. Asymmetric warfare and the new focus on small, agile forces has altered the framework by which time critical information is digested and acted upon by decision makers. Finding and integrating decision-relevant information is increasingly difficult in data-dense environments. In this new information environment, agile data algorithms, machine learning software, and threat alert mechanisms must be developed to automatically create alerts and drive quick response. Yet these advanced technologies must be balanced with awareness of the underlying context to accurately interpret machine-processed indicators and warnings and recommendations. One promising approach to this challenge brings together information retrieval strategies from text, video, and imagery. In this paper, we describe a technology demonstration that represents two years of tri-service research seeking to meld text and video for enhanced content awareness. The demonstration used multisource data to find an intelligence solution to a problem using a common dataset. Three technology highlights from this effort include 1) Incorporation of external sources of context into imagery normalcy modeling and anomaly detection capabilities, 2) Automated discovery and monitoring of targeted users from social media text, regardless of language, and 3) The concurrent use of text and imagery to characterize behaviour using the concept of kinematic and text motifs to detect novel and anomalous patterns. Our demonstration provided a technology baseline for exploiting heterogeneous data sources to deliver timely and accurate synopses of data that contribute to a dynamic and comprehensive worldview.

  13. Coding visual features extracted from video sequences.

    Science.gov (United States)

    Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

    2014-05-01

    Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

  14. Extractive text summarization system to aid data extraction from full text in systematic review development.

    Science.gov (United States)

    Bui, Duy Duc An; Del Fiol, Guilherme; Hurdle, John F; Jonnalagadda, Siddhartha

    2016-12-01

    Extracting data from publication reports is a standard process in systematic review (SR) development. However, the data extraction process still relies too much on manual effort which is slow, costly, and subject to human error. In this study, we developed a text summarization system aimed at enhancing productivity and reducing errors in the traditional data extraction process. We developed a computer system that used machine learning and natural language processing approaches to automatically generate summaries of full-text scientific publications. The summaries at the sentence and fragment levels were evaluated in finding common clinical SR data elements such as sample size, group size, and PICO values. We compared the computer-generated summaries with human written summaries (title and abstract) in terms of the presence of necessary information for the data extraction as presented in the Cochrane review's study characteristics tables. At the sentence level, the computer-generated summaries covered more information than humans do for systematic reviews (recall 91.2% vs. 83.8%, p<0.001). They also had a better density of relevant sentences (precision 59% vs. 39%, p<0.001). At the fragment level, the ensemble approach combining rule-based, concept mapping, and dictionary-based methods performed better than individual methods alone, achieving an 84.7% F-measure. Computer-generated summaries are potential alternative information sources for data extraction in systematic review development. Machine learning and natural language processing are promising approaches to the development of such an extractive summarization system. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Keyword Extraction from Arabic Legal Texts

    Science.gov (United States)

    Rammal, Mahmoud; Bahsoun, Zeinab; Al Achkar Jabbour, Mona

    2015-01-01

    Purpose: The purpose of this paper is to apply local grammar (LG) to develop an indexing system which automatically extracts keywords from titles of Lebanese official journals. Design/methodology/approach: To build LG for our system, the first word that plays the determinant role in understanding the meaning of a title is analyzed and grouped as…

  16. Text Character Extraction Implementation from Captured Handwritten Image to Text Conversionusing Template Matching Technique

    Directory of Open Access Journals (Sweden)

    Barate Seema

    2016-01-01

    Full Text Available Images contain various types of useful information that should be extracted whenever required. A various algorithms and methods are proposed to extract text from the given image, and by using that user will be able to access the text from any image. Variations in text may occur because of differences in size, style,orientation, alignment of text, and low image contrast, composite backgrounds make the problem during extraction of text. If we develop an application that extracts and recognizes those texts accurately in real time, then it can be applied to many important applications like document analysis, vehicle license plate extraction, text- based image indexing, etc and many applications have become realities in recent years. To overcome the above problems we develop such application that will convert the image into text by using algorithms, such as bounding box, HSV model, blob analysis,template matching, template generation.

  17. Scorebox extraction from mobile sports videos using Support Vector Machines

    Science.gov (United States)

    Kim, Wonjun; Park, Jimin; Kim, Changick

    2008-08-01

    Scorebox plays an important role in understanding contents of sports videos. However, the tiny scorebox may give the small-display-viewers uncomfortable experience in grasping the game situation. In this paper, we propose a novel framework to extract the scorebox from sports video frames. We first extract candidates by using accumulated intensity and edge information after short learning period. Since there are various types of scoreboxes inserted in sports videos, multiple attributes need to be used for efficient extraction. Based on those attributes, the optimal information gain is computed and top three ranked attributes in terms of information gain are selected as a three-dimensional feature vector for Support Vector Machines (SVM) to distinguish the scorebox from other candidates, such as logos and advertisement boards. The proposed method is tested on various videos of sports games and experimental results show the efficiency and robustness of our proposed method.

  18. Mining knowledge from text repositories using information extraction ...

    Indian Academy of Sciences (India)

    Information extraction (IE); text mining; text repositories; knowledge discovery from .... general purpose English words. However ... of precision and recall, as extensive experimentation is required due to lack of public tagged corpora. 4. Mining ...

  19. If a Picture Is Worth a Thousand Words Is Video Worth a Million? Differences in Affective and Cognitive Processing of Video and Text Cases

    Science.gov (United States)

    Yadav, Aman; Phillips, Michael M.; Lundeberg, Mary A.; Koehler, Matthew J.; Hilden, Katherine; Dirkin, Kathryn H.

    2011-01-01

    In this investigation we assessed whether different formats of media (video, text, and video + text) influenced participants' engagement, cognitive processing and recall of non-fiction cases of people diagnosed with HIV/AIDS. For each of the cases used in the study, we designed three informationally-equivalent versions: video, text, and video +…

  20. Text feature extraction based on deep learning: a review.

    Science.gov (United States)

    Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

    2017-01-01

    Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

  1. Layout-aware text extraction from full-text PDF of scientific articles.

    Science.gov (United States)

    Ramakrishnan, Cartic; Patnia, Abhishek; Hovy, Eduard; Burns, Gully Apc

    2012-05-28

    The Portable Document Format (PDF) is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the 'Layout-Aware PDF Text Extraction' (LA-PDFText) system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1) Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2) Classifying text blocks into rhetorical categories using a rule-based method and (3) Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF. Finally, we discuss preliminary error analysis for

  2. Parallel Key Frame Extraction for Surveillance Video Service in a Smart City.

    Directory of Open Access Journals (Sweden)

    Ran Zheng

    Full Text Available Surveillance video service (SVS is one of the most important services provided in a smart city. It is very important for the utilization of SVS to provide design efficient surveillance video analysis techniques. Key frame extraction is a simple yet effective technique to achieve this goal. In surveillance video applications, key frames are typically used to summarize important video content. It is very important and essential to extract key frames accurately and efficiently. A novel approach is proposed to extract key frames from traffic surveillance videos based on GPU (graphics processing units to ensure high efficiency and accuracy. For the determination of key frames, motion is a more salient feature in presenting actions or events, especially in surveillance videos. The motion feature is extracted in GPU to reduce running time. It is also smoothed to reduce noise, and the frames with local maxima of motion information are selected as the final key frames. The experimental results show that this approach can extract key frames more accurately and efficiently compared with several other methods.

  3. Layout-aware text extraction from full-text PDF of scientific articles

    Directory of Open Access Journals (Sweden)

    Ramakrishnan Cartic

    2012-05-01

    Full Text Available Abstract Background The Portable Document Format (PDF is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the ‘Layout-Aware PDF Text Extraction’ (LA-PDFText system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Results Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1 Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2 Classifying text blocks into rhetorical categories using a rule-based method and (3 Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF

  4. Semantic Information Extraction of Lanes Based on Onboard Camera Videos

    Science.gov (United States)

    Tang, L.; Deng, T.; Ren, C.

    2018-04-01

    In the field of autonomous driving, semantic information of lanes is very important. This paper proposes a method of automatic detection of lanes and extraction of semantic information from onboard camera videos. The proposed method firstly detects the edges of lanes by the grayscale gradient direction, and improves the Probabilistic Hough transform to fit them; then, it uses the vanishing point principle to calculate the lane geometrical position, and uses lane characteristics to extract lane semantic information by the classification of decision trees. In the experiment, 216 road video images captured by a camera mounted onboard a moving vehicle were used to detect lanes and extract lane semantic information. The results show that the proposed method can accurately identify lane semantics from video images.

  5. Automatic Definition Extraction and Crossword Generation From Spanish News Text

    Directory of Open Access Journals (Sweden)

    Jennifer Esteche

    2017-08-01

    Full Text Available This paper describes the design and implementation of a system that takes Spanish texts and generates crosswords (board and definitions in a fully automatic way using definitions extracted from those texts. Our solution divides the problem in two parts: a definition extraction module that applies pattern matching implemented in Python, and a crossword generation module that uses a greedy strategy implemented in Prolog. The system achieves 73% precision and builds crosswords similar to those built by humans.

  6. Rational kernels for Arabic Root Extraction and Text Classification

    Directory of Open Access Journals (Sweden)

    Attia Nehar

    2016-04-01

    Full Text Available In this paper, we address the problems of Arabic Text Classification and root extraction using transducers and rational kernels. We introduce a new root extraction approach on the basis of the use of Arabic patterns (Pattern Based Stemmer. Transducers are used to model these patterns and root extraction is done without relying on any dictionary. Using transducers for extracting roots, documents are transformed into finite state transducers. This document representation allows us to use and explore rational kernels as a framework for Arabic Text Classification. Root extraction experiments are conducted on three word collections and yield 75.6% of accuracy. Classification experiments are done on the Saudi Press Agency dataset and N-gram kernels are tested with different values of N. Accuracy and F1 report 90.79% and 62.93% respectively. These results show that our approach, when compared with other approaches, is promising specially in terms of accuracy and F1.

  7. Big Data Analytics: Challenges And Applications For Text, Audio, Video, And Social Media Data

    OpenAIRE

    Jai Prakash Verma; Smita Agrawal; Bankim Patel; Atul Patel

    2016-01-01

    All types of machine automated systems are generating large amount of data in different forms like statistical, text, audio, video, sensor, and bio-metric data that emerges the term Big Data. In this paper we are discussing issues, challenges, and application of these types of Big Data with the consideration of big data dimensions. Here we are discussing social media data analytics, content based analytics, text data analytics, audio, and video data analytics their issues and expected applica...

  8. Patient perceptions of text-messages, email, and video in dermatologic surgery patients.

    Science.gov (United States)

    Hawkins, Spencer D; Barilla, Steven; Williford, Phillip Williford M; Feldman, Steven R; Pearce, Daniel J

    2017-04-14

    We developed dermatology patient education videos and a post-operative text message service that could be accessed universally via web based applications. A secondary outcome of the study was to assess patient opinions of text-messages, email, and video in the health care setting which is reported here. An investigator-blinded, randomized, controlled intervention was evaluated in 90 nonmelanoma MMS patients at Wake Forest Baptist Dermatology. Patients were randomized 1:1:1:1 for exposure to: 1) videos with text messages, 2) videos only, 3) text messages-only, or 4) standard of care. Assessment measures were obtained by the use of REDCap survey questions during the follow up visit. 1) 67% would like to receive an email with information about the procedure beforehand 2) 98% of patients reported they would like other doctors to use educational videos as a form of patient education 3) 88% of our patients think it is appropriate for physicians to communicate to patients via text message in certain situations. Nearly all patients desired physicians to use text-messages and video in their practice and the majority of patients preferred to receive an email with information about their procedure beforehand.

  9. Evaluation on the use of animated narrative video in teaching narrative text

    Directory of Open Access Journals (Sweden)

    Soe’oed Rahmat

    2018-01-01

    Full Text Available In the 21st century, our life is strongly affected by the information technology. Educational technology has been rapidly improved by the development of audiovisual tools. Teachers may choose a number of different types of resources for teaching purposes, including videos and movies. Therefore, this study is aimed at evaluating animated narrative videos from YouTube for the teaching narrative text and identifying potential factors which influence the quality of educational videos. The videos were examined by using assessment rubric to see the quality and suitability of animated narrative videos which might be used in the teaching narrative text. The rubric was adapted from Prince Edward Island (PEI Department of Education: Evaluation and Selection of Learning Resources. It consists of four criteria, content, structure, instructional design, and technical design In addition, the study presents critical awareness of how these aspects can be interpreted to measure animated narrative videos and at the same time the engagement of the teachers in exploring animated narrative videos used in classroom.

  10. Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

    Directory of Open Access Journals (Sweden)

    Gil-beom Lee

    2017-03-01

    Full Text Available Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos.

  11. Enhancing biomedical text summarization using semantic relation extraction.

    Directory of Open Access Journals (Sweden)

    Yue Shang

    Full Text Available Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1 We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2 We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3 For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

  12. A text-mining system for extracting metabolic reactions from full-text articles.

    Science.gov (United States)

    Czarnecki, Jan; Nobeli, Irene; Smith, Adrian M; Shepherd, Adrian J

    2012-07-23

    Increasingly biological text mining research is focusing on the extraction of complex relationships relevant to the construction and curation of biological networks and pathways. However, one important category of pathway - metabolic pathways - has been largely neglected.Here we present a relatively simple method for extracting metabolic reaction information from free text that scores different permutations of assigned entities (enzymes and metabolites) within a given sentence based on the presence and location of stemmed keywords. This method extends an approach that has proved effective in the context of the extraction of protein-protein interactions. When evaluated on a set of manually-curated metabolic pathways using standard performance criteria, our method performs surprisingly well. Precision and recall rates are comparable to those previously achieved for the well-known protein-protein interaction extraction task. We conclude that automated metabolic pathway construction is more tractable than has often been assumed, and that (as in the case of protein-protein interaction extraction) relatively simple text-mining approaches can prove surprisingly effective. It is hoped that these results will provide an impetus to further research and act as a useful benchmark for judging the performance of more sophisticated methods that are yet to be developed.

  13. Enhancing biomedical text summarization using semantic relation extraction.

    Science.gov (United States)

    Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

    2011-01-01

    Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

  14. Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Buch SV

    2014-08-01

    Full Text Available Steen Vigh Buch,1 Frederik Philip Treschow,2 Jesper Brink Svendsen,3 Bjarne Skjødt Worm4 1Department of Vascular Surgery, Rigshospitalet, Copenhagen, Denmark; 2Department of Anesthesia and Intensive Care, Herlev Hospital, Copenhagen, Denmark; 3Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 4Department of Anesthesia and Intensive Care, Bispebjerg Hospital, Copenhagen, Denmark Background and aims: This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Materials and methods: Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. Results: The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001 and in the follow-up test (P<0.01. Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04. Conclusion: Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills. Keywords: e-learning, video versus text, medicine, clinical skills

  15. Knowledge Dictionary for Information Extraction on the Arabic Text Data

    Directory of Open Access Journals (Sweden)

    Wahyu Jauharis Saputra

    2013-04-01

    Full Text Available Information extraction is an early stage of a process of textual data analysis. Information extraction is required to get information from textual data that can be used for process analysis, such as classification and categorization. A textual data is strongly influenced by the language. Arabic is gaining a significant attention in many studies because Arabic language is very different from others, and in contrast to other languages, tools and research on the Arabic language is still lacking. The information extracted using the knowledge dictionary is a concept of expression. A knowledge dictionary is usually constructed manually by an expert and this would take a long time and is specific to a problem only. This paper proposed a method for automatically building a knowledge dictionary. Dictionary knowledge is formed by classifying sentences having the same concept, assuming that they will have a high similarity value. The concept that has been extracted can be used as features for subsequent computational process such as classification or categorization. Dataset used in this paper was the Arabic text dataset. Extraction result was tested by using a decision tree classification engine and the highest precision value obtained was 71.0% while the highest recall value was 75.0%. 

  16. METHOD OF RARE TERM CONTRASTIVE EXTRACTION FROM NATURAL LANGUAGE TEXTS

    Directory of Open Access Journals (Sweden)

    I. A. Bessmertny

    2017-01-01

    Full Text Available The paper considers a problem of automatic domain term extraction from documents corpus by means of a contrast collection. Existing contrastive methods successfully extract often used terms but mishandle rare terms. This could yield poorness of the resulting thesaurus. Assessment of point-wise mutual information is one of the known statistical methods of term extraction and it finds rare terms successfully. Although, it extracts many false terms at that. The proposed approach consists of point-wise mutual information application for rare terms extraction and filtering of candidates by criterion of joint occurrence with the other candidates. We build “documents-by-terms” matrix that is subjected to singular value decomposition to eliminate noise and reveal strong interconnections. Then we pass on to the resulting matrix “terms-by-terms” that reproduces strength of interconnections between words. This approach was approved on a documents collection from “Geology” domain with the use of contrast documents from such topics as “Politics”, “Culture”, “Economics” and “Accidents” on some Internet resources. The experimental results demonstrate operability of this method for rare terms extraction.

  17. Multimodal Semantics Extraction from User-Generated Videos

    Directory of Open Access Journals (Sweden)

    Francesco Cricri

    2012-01-01

    Full Text Available User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order to obtain semantic information about public happenings (e.g., sport and live music events being recorded in these videos. One of the key contributions of this work is a joint utilization of different data modalities, including such captured by auxiliary sensors during the video recording performed by each user. In particular, we analyze GPS data, magnetometer data, accelerometer data, video- and audio-content data. We use these data modalities to infer information about the event being recorded, in terms of layout (e.g., stadium, genre, indoor versus outdoor scene, and the main area of interest of the event. Furthermore we propose a method that automatically identifies the optimal set of cameras to be used in a multicamera video production. Finally, we detect the camera users which fall within the field of view of other cameras recording at the same public happening. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real sport events and live music performances.

  18. Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial.

    Science.gov (United States)

    Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

    2014-01-01

    This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (Pvideo group performed better on the follow-up test (P=0.04). Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills.

  19. NAMED ENTITY RECOGNITION FROM BIOMEDICAL TEXT -AN INFORMATION EXTRACTION TASK

    Directory of Open Access Journals (Sweden)

    N. Kanya

    2016-07-01

    Full Text Available Biomedical Text Mining targets the Extraction of significant information from biomedical archives. Bio TM encompasses Information Retrieval (IR and Information Extraction (IE. The Information Retrieval will retrieve the relevant Biomedical Literature documents from the various Repositories like PubMed, MedLine etc., based on a search query. The IR Process ends up with the generation of corpus with the relevant document retrieved from the Publication databases based on the query. The IE task includes the process of Preprocessing of the document, Named Entity Recognition (NER from the documents and Relationship Extraction. This process includes Natural Language Processing, Data Mining techniques and machine Language algorithm. The preprocessing task includes tokenization, stop word Removal, shallow parsing, and Parts-Of-Speech tagging. NER phase involves recognition of well-defined objects such as genes, proteins or cell-lines etc. This process leads to the next phase that is extraction of relationships (IE. The work was based on machine learning algorithm Conditional Random Field (CRF.

  20. Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction

    Directory of Open Access Journals (Sweden)

    Darko Brodić

    2010-05-01

    Full Text Available Text line segmentation is an essential stage in off-line optical character recognition (OCR systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms.

  1. Extracting BI-RADS Features from Portuguese Clinical Texts.

    Science.gov (United States)

    Nassif, Houssam; Cunha, Filipe; Moreira, Inês C; Cruz-Correia, Ricardo; Sousa, Eliana; Page, David; Burnside, Elizabeth; Dutra, Inês

    2012-01-01

    In this work we build the first BI-RADS parser for Portuguese free texts, modeled after existing approaches to extract BI-RADS features from English medical records. Our concept finder uses a semantic grammar based on the BIRADS lexicon and on iterative transferred expert knowledge. We compare the performance of our algorithm to manual annotation by a specialist in mammography. Our results show that our parser's performance is comparable to the manual method.

  2. DEXTER: Disease-Expression Relation Extraction from Text.

    Science.gov (United States)

    Gupta, Samir; Dingerdissen, Hayley; Ross, Karen E; Hu, Yu; Wu, Cathy H; Mazumder, Raja; Vijay-Shanker, K

    2018-01-01

    Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression-disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our text-mined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential expression information for 2024 genes in lung

  3. Using Text Mining to Uncover Students' Technology-Related Problems in Live Video Streaming

    Science.gov (United States)

    Abdous, M'hammed; He, Wu

    2011-01-01

    Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streaming (LVS) students' technology related-problems and to…

  4. Automatic extraction of ontological relations from Arabic text

    Directory of Open Access Journals (Sweden)

    Mohammed G.H. Al Zamil

    2014-12-01

    The proposed methodology has been designed to analyze Arabic text using lexical semantic patterns of the Arabic language according to a set of features. Next, the features have been abstracted and enriched with formal descriptions for the purpose of generalizing the resulted rules. The rules, then, have formulated a classifier that accepts Arabic text, analyzes it, and then displays related concepts labeled with its designated relationship. Moreover, to resolve the ambiguity of homonyms, a set of machine translation, text mining, and part of speech tagging algorithms have been reused. We performed extensive experiments to measure the effectiveness of our proposed tools. The results indicate that our proposed methodology is promising for automating the process of extracting ontological relations.

  5. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....

  6. Medical Ultrasound Video Coding with H.265/HEVC Based on ROI Extraction.

    Directory of Open Access Journals (Sweden)

    Yueying Wu

    Full Text Available High-efficiency video compression technology is of primary importance to the storage and transmission of digital medical video in modern medical communication systems. To further improve the compression performance of medical ultrasound video, two innovative technologies based on diagnostic region-of-interest (ROI extraction using the high efficiency video coding (H.265/HEVC standard are presented in this paper. First, an effective ROI extraction algorithm based on image textural features is proposed to strengthen the applicability of ROI detection results in the H.265/HEVC quad-tree coding structure. Second, a hierarchical coding method based on transform coefficient adjustment and a quantization parameter (QP selection process is designed to implement the otherness encoding for ROIs and non-ROIs. Experimental results demonstrate that the proposed optimization strategy significantly improves the coding performance by achieving a BD-BR reduction of 13.52% and a BD-PSNR gain of 1.16 dB on average compared to H.265/HEVC (HM15.0. The proposed medical video coding algorithm is expected to satisfy low bit-rate compression requirements for modern medical communication systems.

  7. Mobile Message Services Using Text, Audio or Video for Improving the Learning Infrastructure in Higher Education

    Directory of Open Access Journals (Sweden)

    Björn Olof Hedin

    2006-06-01

    Full Text Available This study examines how media files sent to mobile phones can be used to improve education at universities, and describes a prototype implement of such a system using standard components. To accomplish this, university students were equipped with mobile phones and software that allowed teachers to send text-based, audio-based and video-based messages to the students. Data was collected using questionnaires, focus groups and log files. The conclusions were that students preferred to have information and learning content sent as text, rather than audio or video. Text messages sent to phones should be no longer than 2000 characters. The most appreciated services were notifications of changes in course schedules, short lecture introductions and reminders. The prototype showed that this functionality is easy to implement using standard components.

  8. Pharmspresso: a text mining tool for extraction of pharmacogenomic concepts and relationships from full text.

    Science.gov (United States)

    Garten, Yael; Altman, Russ B

    2009-02-05

    Pharmacogenomics studies the relationship between genetic variation and the variation in drug response phenotypes. The field is rapidly gaining importance: it promises drugs targeted to particular subpopulations based on genetic background. The pharmacogenomics literature has expanded rapidly, but is dispersed in many journals. It is challenging, therefore, to identify important associations between drugs and molecular entities--particularly genes and gene variants, and thus these critical connections are often lost. Text mining techniques can allow us to convert the free-style text to a computable, searchable format in which pharmacogenomic concepts (such as genes, drugs, polymorphisms, and diseases) are identified, and important links between these concepts are recorded. Availability of full text articles as input into text mining engines is key, as literature abstracts often do not contain sufficient information to identify these pharmacogenomic associations. Thus, building on a tool called Textpresso, we have created the Pharmspresso tool to assist in identifying important pharmacogenomic facts in full text articles. Pharmspresso parses text to find references to human genes, polymorphisms, drugs and diseases and their relationships. It presents these as a series of marked-up text fragments, in which key concepts are visually highlighted. To evaluate Pharmspresso, we used a gold standard of 45 human-curated articles. Pharmspresso identified 78%, 61%, and 74% of target gene, polymorphism, and drug concepts, respectively. Pharmspresso is a text analysis tool that extracts pharmacogenomic concepts from the literature automatically and thus captures our current understanding of gene-drug interactions in a computable form. We have made Pharmspresso available at http://pharmspresso.stanford.edu.

  9. Domain-independent information extraction in unstructured text

    Energy Technology Data Exchange (ETDEWEB)

    Irwin, N.H. [Sandia National Labs., Albuquerque, NM (United States). Software Surety Dept.

    1996-09-01

    Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.

  10. Automated Extraction of Substance Use Information from Clinical Texts.

    Science.gov (United States)

    Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

    2015-01-01

    Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

  11. Using Semantic Linking to Understand Persons’ Networks Extracted from Text

    Directory of Open Access Journals (Sweden)

    Alessio Palmero Aprosio

    2017-11-01

    Full Text Available In this work, we describe a methodology to interpret large persons’ networks extracted from text by classifying cliques using the DBpedia ontology. The approach relies on a combination of NLP, Semantic web technologies, and network analysis. The classification methodology that first starts from single nodes and then generalizes to cliques is effective in terms of performance and is able to deal also with nodes that are not linked to Wikipedia. The gold standard manually developed for evaluation shows that groups of co-occurring entities share in most of the cases a category that can be automatically assigned. This holds for both languages considered in this study. The outcome of this work may be of interest to enhance the readability of large networks and to provide an additional semantic layer on top of cliques. This would greatly help humanities scholars when dealing with large amounts of textual data that need to be interpreted or categorized. Furthermore, it represents an unsupervised approach to automatically extend DBpedia starting from a corpus.

  12. Students' Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video

    DEFF Research Database (Denmark)

    Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte

    2017-01-01

    OBJECTIVES: The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students......' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. METHODS: The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed...

  13. First- and third-party ground truth for key frame extraction from consumer video clips

    Science.gov (United States)

    Costello, Kathleen; Luo, Jiebo

    2007-02-01

    Extracting key frames (KF) from video is of great interest in many applications, such as video summary, video organization, video compression, and prints from video. KF extraction is not a new problem. However, current literature has been focused mainly on sports or news video. In the consumer video space, the biggest challenges for key frame selection from consumer videos are the unconstrained content and lack of any preimposed structure. In this study, we conduct ground truth collection of key frames from video clips taken by digital cameras (as opposed to camcorders) using both first- and third-party judges. The goals of this study are: (1) to create a reference database of video clips reasonably representative of the consumer video space; (2) to identify associated key frames by which automated algorithms can be compared and judged for effectiveness; and (3) to uncover the criteria used by both first- and thirdparty human judges so these criteria can influence algorithm design. The findings from these ground truths will be discussed.

  14. Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

    Science.gov (United States)

    Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

    2012-04-01

    In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

  15. Visual content highlighting via automatic extraction of embedded captions on MPEG compressed video

    Science.gov (United States)

    Yeo, Boon-Lock; Liu, Bede

    1996-03-01

    Embedded captions in TV programs such as news broadcasts, documentaries and coverage of sports events provide important information on the underlying events. In digital video libraries, such captions represent a highly condensed form of key information on the contents of the video. In this paper we propose a scheme to automatically detect the presence of captions embedded in video frames. The proposed method operates on reduced image sequences which are efficiently reconstructed from compressed MPEG video and thus does not require full frame decompression. The detection, extraction and analysis of embedded captions help to capture the highlights of visual contents in video documents for better organization of video, to present succinctly the important messages embedded in the images, and to facilitate browsing, searching and retrieval of relevant clips.

  16. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

    Directory of Open Access Journals (Sweden)

    Florian Eyben

    Full Text Available Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

  17. Parallel Key Frame Extraction for Surveillance Video Service in a Smart City.

    Science.gov (United States)

    Zheng, Ran; Yao, Chuanwei; Jin, Hai; Zhu, Lei; Zhang, Qin; Deng, Wei

    2015-01-01

    Surveillance video service (SVS) is one of the most important services provided in a smart city. It is very important for the utilization of SVS to provide design efficient surveillance video analysis techniques. Key frame extraction is a simple yet effective technique to achieve this goal. In surveillance video applications, key frames are typically used to summarize important video content. It is very important and essential to extract key frames accurately and efficiently. A novel approach is proposed to extract key frames from traffic surveillance videos based on GPU (graphics processing units) to ensure high efficiency and accuracy. For the determination of key frames, motion is a more salient feature in presenting actions or events, especially in surveillance videos. The motion feature is extracted in GPU to reduce running time. It is also smoothed to reduce noise, and the frames with local maxima of motion information are selected as the final key frames. The experimental results show that this approach can extract key frames more accurately and efficiently compared with several other methods.

  18. Text extraction method for historical Tibetan document images based on block projections

    Science.gov (United States)

    Duan, Li-juan; Zhang, Xi-qun; Ma, Long-long; Wu, Jian

    2017-11-01

    Text extraction is an important initial step in digitizing the historical documents. In this paper, we present a text extraction method for historical Tibetan document images based on block projections. The task of text extraction is considered as text area detection and location problem. The images are divided equally into blocks and the blocks are filtered by the information of the categories of connected components and corner point density. By analyzing the filtered blocks' projections, the approximate text areas can be located, and the text regions are extracted. Experiments on the dataset of historical Tibetan documents demonstrate the effectiveness of the proposed method.

  19. Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

    Directory of Open Access Journals (Sweden)

    Andrea Cavallaro

    2004-06-01

    Full Text Available The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into low-level and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one “sees” in a scene depends on the scene itself (region segmentation as well as on the cognitive task (semantic segmentation at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an N-dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to

  20. A Comparison of Video Modeling, Text-Based Instruction, and No Instruction for Creating Multiple Baseline Graphs in Microsoft Excel

    Science.gov (United States)

    Tyner, Bryan C.; Fienup, Daniel M.

    2015-01-01

    Graphing is socially significant for behavior analysts; however, graphing can be difficult to learn. Video modeling (VM) may be a useful instructional method but lacks evidence for effective teaching of computer skills. A between-groups design compared the effects of VM, text-based instruction, and no instruction on graphing performance.…

  1. Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

    Directory of Open Access Journals (Sweden)

    Li Yao

    2016-01-01

    Full Text Available Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.

  2. Tagline: Information Extraction for Semi-Structured Text Elements in Medical Progress Notes

    Science.gov (United States)

    Finch, Dezon Kile

    2012-01-01

    Text analysis has become an important research activity in the Department of Veterans Affairs (VA). Statistical text mining and natural language processing have been shown to be very effective for extracting useful information from medical documents. However, neither of these techniques is effective at extracting the information stored in…

  3. Extracting foreground ensemble features to detect abnormal crowd behavior in intelligent video-surveillance systems

    Science.gov (United States)

    Chan, Yi-Tung; Wang, Shuenn-Jyi; Tsai, Chung-Hsien

    2017-09-01

    Public safety is a matter of national security and people's livelihoods. In recent years, intelligent video-surveillance systems have become important active-protection systems. A surveillance system that provides early detection and threat assessment could protect people from crowd-related disasters and ensure public safety. Image processing is commonly used to extract features, e.g., people, from a surveillance video. However, little research has been conducted on the relationship between foreground detection and feature extraction. Most current video-surveillance research has been developed for restricted environments, in which the extracted features are limited by having information from a single foreground; they do not effectively represent the diversity of crowd behavior. This paper presents a general framework based on extracting ensemble features from the foreground of a surveillance video to analyze a crowd. The proposed method can flexibly integrate different foreground-detection technologies to adapt to various monitored environments. Furthermore, the extractable representative features depend on the heterogeneous foreground data. Finally, a classification algorithm is applied to these features to automatically model crowd behavior and distinguish an abnormal event from normal patterns. The experimental results demonstrate that the proposed method's performance is both comparable to that of state-of-the-art methods and satisfies the requirements of real-time applications.

  4. Impact of Interactive Video Communication Versus Text-Based Feedback on Teaching, Social, and Cognitive Presence in Online Learning Communities.

    Science.gov (United States)

    Seckman, Charlotte

    A key element to online learning is the ability to create a sense of presence to improve learning outcomes. This quasi-experimental study evaluated the impact of interactive video communication versus text-based feedback and found a significant difference between the 2 groups related to teaching, social, and cognitive presence. Recommendations to enhance presence should focus on providing timely feedback, interactive learning experiences, and opportunities for students to establish relationships with peers and faculty.

  5. Students' Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video: A Qualitative Study.

    Science.gov (United States)

    Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte; Mors, Ole; Ringsted, Charlotte; Morcke, Anne Mette

    2017-10-06

    The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed interviews. Students taught with text-based patient cases emphasized excitement and drama towards the personal clinical narratives presented by the teachers during the course, but never referred to the patient cases. Authority and boundary setting were regarded as important in managing patients. Students taught with video-based patient cases, in contrast, often referred to the patient cases when highlighting new insights, including the importance of patient perspectives when communicating with patients. The format of patient cases included in teaching may have a substantial impact on students' patient-centeredness. Video-based patient cases are probably more effective than text-based patient cases in fostering patient-centered perspectives in medical students. Teachers sharing stories from their own clinical experiences stimulates both engagement and excitement, but may also provoke unintended stigma and influence an authoritative approach in medical students towards managing patients in clinical psychiatry.

  6. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

    Directory of Open Access Journals (Sweden)

    Abdul Wahab Muzaffar

    2015-01-01

    Full Text Available The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

  7. Medical Ultrasound Video Coding with H.265/HEVC Based on ROI Extraction.

    Science.gov (United States)

    Wu, Yueying; Liu, Pengyu; Gao, Yuan; Jia, Kebin

    2016-01-01

    High-efficiency video compression technology is of primary importance to the storage and transmission of digital medical video in modern medical communication systems. To further improve the compression performance of medical ultrasound video, two innovative technologies based on diagnostic region-of-interest (ROI) extraction using the high efficiency video coding (H.265/HEVC) standard are presented in this paper. First, an effective ROI extraction algorithm based on image textural features is proposed to strengthen the applicability of ROI detection results in the H.265/HEVC quad-tree coding structure. Second, a hierarchical coding method based on transform coefficient adjustment and a quantization parameter (QP) selection process is designed to implement the otherness encoding for ROIs and non-ROIs. Experimental results demonstrate that the proposed optimization strategy significantly improves the coding performance by achieving a BD-BR reduction of 13.52% and a BD-PSNR gain of 1.16 dB on average compared to H.265/HEVC (HM15.0). The proposed medical video coding algorithm is expected to satisfy low bit-rate compression requirements for modern medical communication systems.

  8. Lithium NLP: A System for Rich Information Extraction from Noisy User Generated Text on Social Media

    OpenAIRE

    Bhargava, Preeti; Spasojevic, Nemanja; Hu, Guoning

    2017-01-01

    In this paper, we describe the Lithium Natural Language Processing (NLP) system - a resource-constrained, high- throughput and language-agnostic system for information extraction from noisy user generated text on social media. Lithium NLP extracts a rich set of information including entities, topics, hashtags and sentiment from text. We discuss several real world applications of the system currently incorporated in Lithium products. We also compare our system with existing commercial and acad...

  9. A comparison of video modeling, text-based instruction, and no instruction for creating multiple baseline graphs in Microsoft Excel.

    Science.gov (United States)

    Tyner, Bryan C; Fienup, Daniel M

    2015-09-01

    Graphing is socially significant for behavior analysts; however, graphing can be difficult to learn. Video modeling (VM) may be a useful instructional method but lacks evidence for effective teaching of computer skills. A between-groups design compared the effects of VM, text-based instruction, and no instruction on graphing performance. Participants who used VM constructed graphs significantly faster and with fewer errors than those who used text-based instruction or no instruction. Implications for instruction are discussed. © Society for the Experimental Analysis of Behavior.

  10. BioFoV - An open platform for forensic video analysis and biometric data extraction

    DEFF Research Database (Denmark)

    Almeida, Miguel; Correia, Paulo Lobato; Larsen, Peter Kastmand

    2016-01-01

    to tailor-made software, based on state of art knowledge in fields such as soft biometrics, gait recognition, photogrammetry, etc. This paper proposes an open and extensible platform, BioFoV (Biometric Forensic Video tool), for forensic video analysis and biometric data extraction, aiming to host some...... of the developments that researchers come up with for solving specific problems, but that are often not shared with the community. BioFoV includes a simple to use Graphical User Interface (GUI), is implemented with open software that can run in multiple software platforms, and its implementation is publicly available....

  11. Extracting of implicit information in English advertising texts with phonetic and lexical-morphological means

    Directory of Open Access Journals (Sweden)

    Traikovskaya Natalya Petrovna

    2015-12-01

    Full Text Available The article deals with phonetic and lexical-morphological language means participating in the process of extracting implicit information in English-speaking advertising texts for men and women. The functioning of phonetic means of the English language is not the basis for implication of information in advertising texts. Lexical and morphological means play the role of markers of relevant information, playing the role of the activator ofimplicit information in the texts of advertising.

  12. Big data extraction with adaptive wavelet analysis (Presentation Video)

    Science.gov (United States)

    Qu, Hongya; Chen, Genda; Ni, Yiqing

    2015-04-01

    Nondestructive evaluation and sensing technology have been increasingly applied to characterize material properties and detect local damage in structures. More often than not, they generate images or data strings that are difficult to see any physical features without novel data extraction techniques. In the literature, popular data analysis techniques include Short-time Fourier Transform, Wavelet Transform, and Hilbert Transform for time efficiency and adaptive recognition. In this study, a new data analysis technique is proposed and developed by introducing an adaptive central frequency of the continuous Morlet wavelet transform so that both high frequency and time resolution can be maintained in a time-frequency window of interest. The new analysis technique is referred to as Adaptive Wavelet Analysis (AWA). This paper will be organized in several sections. In the first section, finite time-frequency resolution limitations in the traditional wavelet transform are introduced. Such limitations would greatly distort the transformed signals with a significant frequency variation with time. In the second section, Short Time Wavelet Transform (STWT), similar to Short Time Fourier Transform (STFT), is defined and developed to overcome such shortcoming of the traditional wavelet transform. In the third section, by utilizing the STWT and a time-variant central frequency of the Morlet wavelet, AWA can adapt the time-frequency resolution requirement to the signal variation over time. Finally, the advantage of the proposed AWA is demonstrated in Section 4 with a ground penetrating radar (GPR) image from a bridge deck, an analytical chirp signal with a large range sinusoidal frequency change over time, the train-induced acceleration responses of the Tsing-Ma Suspension Bridge in Hong Kong, China. The performance of the proposed AWA will be compared with the STFT and traditional wavelet transform.

  13. Mode extraction on wind turbine blades via phase-based video motion estimation

    Science.gov (United States)

    Sarrafi, Aral; Poozesh, Peyman; Niezrecki, Christopher; Mao, Zhu

    2017-04-01

    In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

  14. Using Gazetteers to Extract Sets of Keywords from Free-Flowing Texts

    Directory of Open Access Journals (Sweden)

    Adam Crymble

    2015-12-01

    Full Text Available If you have a copy of a text in electronic format stored on your computer, it is relatively easy to keyword search for a single term. Often you can do this by using the built-in search features in your favourite text editor. However, scholars are increasingly needing to find instances of many terms within a text or texts. For example, a scholar may want to use a gazetteer to extract all mentions of English placenames within a collection of texts so that those places can later be plotted on a map. Alternatively, they may want to extract all male given names, all pronouns, stop words, or any other set of words. Using those same built-in search features to achieve this more complex goal is time consuming and clunky. This lesson will teach you how to use Python to extract a set of keywords very quickly and systematically from a set of texts. It is expected that once you have completed this lesson, you will be able to generalise the skills to extract custom sets of keywords from any set of locally saved files.

  15. Text Chat during Video/Audio Conferencing Lessons: Scaffolding or Getting in the Way?

    Science.gov (United States)

    Kozar, Olga

    2016-01-01

    Private online language tutoring is growing in popularity. An important prerequisite for development of effective pedagogies in this context is a good understanding of how different modalities can be combined. This study provides a detailed account of how several experienced private online teachers use text chat in their Skype-based English…

  16. An unsupervised text mining method for relation extraction from biomedical literature.

    Directory of Open Access Journals (Sweden)

    Changqin Quan

    Full Text Available The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1 Protein-protein interactions extraction, and (2 Gene-suicide association extraction. The evaluation of task (1 on the benchmark dataset (AImed corpus showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on gene-suicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method.

  17. Distractions N' Driving: video game simulation educates young drivers on the dangers of texting while driving.

    Science.gov (United States)

    Saqer, Haneen; de Visser, Ewart; Strohl, Jonathan; Parasuraman, Raja

    2012-01-01

    The proliferation of portable communication and entertainment devices has introduced new dangers to the driving environment, particularly for young and inexperienced drivers. Graduate students from George Mason University illustrate a powerful, practical, and cost-effective program that has been successful in educating these drivers on the dangers of texting while driving, which can easily be adapted and implemented in other communities.

  18. Text mining facilitates database curation - extraction of mutation-disease associations from Bio-medical literature.

    Science.gov (United States)

    Ravikumar, Komandur Elayavilli; Wagholikar, Kavishwar B; Li, Dingcheng; Kocher, Jean-Pierre; Liu, Hongfang

    2015-06-06

    Advances in the next generation sequencing technology has accelerated the pace of individualized medicine (IM), which aims to incorporate genetic/genomic information into medicine. One immediate need in interpreting sequencing data is the assembly of information about genetic variants and their corresponding associations with other entities (e.g., diseases or medications). Even with dedicated effort to capture such information in biological databases, much of this information remains 'locked' in the unstructured text of biomedical publications. There is a substantial lag between the publication and the subsequent abstraction of such information into databases. Multiple text mining systems have been developed, but most of them focus on the sentence level association extraction with performance evaluation based on gold standard text annotations specifically prepared for text mining systems. We developed and evaluated a text mining system, MutD, which extracts protein mutation-disease associations from MEDLINE abstracts by incorporating discourse level analysis, using a benchmark data set extracted from curated database records. MutD achieves an F-measure of 64.3% for reconstructing protein mutation disease associations in curated database records. Discourse level analysis component of MutD contributed to a gain of more than 10% in F-measure when compared against the sentence level association extraction. Our error analysis indicates that 23 of the 64 precision errors are true associations that were not captured by database curators and 68 of the 113 recall errors are caused by the absence of associated disease entities in the abstract. After adjusting for the defects in the curated database, the revised F-measure of MutD in association detection reaches 81.5%. Our quantitative analysis reveals that MutD can effectively extract protein mutation disease associations when benchmarking based on curated database records. The analysis also demonstrates that incorporating

  19. MeInfoText 2.0: gene methylation and cancer relation extraction from biomedical literature

    Directory of Open Access Journals (Sweden)

    Fang Yu-Ching

    2011-12-01

    Full Text Available Abstract Background DNA methylation is regarded as a potential biomarker in the diagnosis and treatment of cancer. The relations between aberrant gene methylation and cancer development have been identified by a number of recent scientific studies. In a previous work, we used co-occurrences to mine those associations and compiled the MeInfoText 1.0 database. To reduce the amount of manual curation and improve the accuracy of relation extraction, we have now developed MeInfoText 2.0, which uses a machine learning-based approach to extract gene methylation-cancer relations. Description Two maximum entropy models are trained to predict if aberrant gene methylation is related to any type of cancer mentioned in the literature. After evaluation based on 10-fold cross-validation, the average precision/recall rates of the two models are 94.7/90.1 and 91.8/90% respectively. MeInfoText 2.0 provides the gene methylation profiles of different types of human cancer. The extracted relations with maximum probability, evidence sentences, and specific gene information are also retrievable. The database is available at http://bws.iis.sinica.edu.tw:8081/MeInfoText2/. Conclusion The previous version, MeInfoText, was developed by using association rules, whereas MeInfoText 2.0 is based on a new framework that combines machine learning, dictionary lookup and pattern matching for epigenetics information extraction. The results of experiments show that MeInfoText 2.0 outperforms existing tools in many respects. To the best of our knowledge, this is the first study that uses a hybrid approach to extract gene methylation-cancer relations. It is also the first attempt to develop a gene methylation and cancer relation corpus.

  20. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus.

    Science.gov (United States)

    Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

    2015-01-01

    Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our annotation is currently limited to a single

  1. Combining automatic table classification and relationship extraction in extracting anticancer drug-side effect pairs from full-text articles.

    Science.gov (United States)

    Xu, Rong; Wang, QuanQiu

    2015-02-01

    Anticancer drug-associated side effect knowledge often exists in multiple heterogeneous and complementary data sources. A comprehensive anticancer drug-side effect (drug-SE) relationship knowledge base is important for computation-based drug target discovery, drug toxicity predication and drug repositioning. In this study, we present a two-step approach by combining table classification and relationship extraction to extract drug-SE pairs from a large number of high-profile oncological full-text articles. The data consists of 31,255 tables downloaded from the Journal of Oncology (JCO). We first trained a statistical classifier to classify tables into SE-related and -unrelated categories. We then extracted drug-SE pairs from SE-related tables. We compared drug side effect knowledge extracted from JCO tables to that derived from FDA drug labels. Finally, we systematically analyzed relationships between anti-cancer drug-associated side effects and drug-associated gene targets, metabolism genes, and disease indications. The statistical table classifier is effective in classifying tables into SE-related and -unrelated (precision: 0.711; recall: 0.941; F1: 0.810). We extracted a total of 26,918 drug-SE pairs from SE-related tables with a precision of 0.605, a recall of 0.460, and a F1 of 0.520. Drug-SE pairs extracted from JCO tables is largely complementary to those derived from FDA drug labels; as many as 84.7% of the pairs extracted from JCO tables have not been included a side effect database constructed from FDA drug labels. Side effects associated with anticancer drugs positively correlate with drug target genes, drug metabolism genes, and disease indications. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Extracting Characteristics of the Study Subjects from Full-Text Articles.

    Science.gov (United States)

    Demner-Fushman, Dina; Mork, James G

    Characteristics of the subjects of biomedical research are important in determining if a publication describing the research is relevant to a search. To facilitate finding relevant publications, MEDLINE citations provide Medical Subject Headings that describe the subjects' characteristics, such as their species, gender, and age. We seek to improve the recommendation of these headings by the Medical Text Indexer (MTI) that supports manual indexing of MEDLINE. To that end, we explore the potential of the full text of the publications. Using simple recall-oriented rule-based methods we determined that adding sentences extracted from the methods sections and captions to the abstracts prior to MTI processing significantly improved recall and F1 score with only a slight drop in precision. Improvements were also achieved in directly assigning several headings extracted from the full text. These results indicate the need for further development of automated methods capable of leveraging the full text for indexing.

  3. Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) final report

    Energy Technology Data Exchange (ETDEWEB)

    Kegelmeyer, Philip W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shead, Timothy M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dunlavy, Daniel M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2013-09-01

    This SAND report summarizes the activities and outcomes of the Network and Ensemble Enabled Entity Extraction in Information Text (NEEEEIT) LDRD project, which addressed improving the accuracy of conditional random fields for named entity recognition through the use of ensemble methods.

  4. Use and Effectiveness of a Video- and Text-Driven Web-Based Computer-Tailored Intervention: Randomized Controlled Trial.

    Science.gov (United States)

    Walthouwer, Michel Jean Louis; Oenema, Anke; Lechner, Lilian; de Vries, Hein

    2015-09-25

    Many Web-based computer-tailored interventions are characterized by high dropout rates, which limit their potential impact. This study had 4 aims: (1) examining if the use of a Web-based computer-tailored obesity prevention intervention can be increased by using videos as the delivery format, (2) examining if the delivery of intervention content via participants' preferred delivery format can increase intervention use, (3) examining if intervention effects are moderated by intervention use and matching or mismatching intervention delivery format preference, (4) and identifying which sociodemographic factors and intervention appreciation variables predict intervention use. Data were used from a randomized controlled study into the efficacy of a video and text version of a Web-based computer-tailored obesity prevention intervention consisting of a baseline measurement and a 6-month follow-up measurement. The intervention consisted of 6 weekly sessions and could be used for 3 months. ANCOVAs were conducted to assess differences in use between the video and text version and between participants allocated to a matching and mismatching intervention delivery format. Potential moderation by intervention use and matching/mismatching delivery format on self-reported body mass index (BMI), physical activity, and energy intake was examined using regression analyses with interaction terms. Finally, regression analysis was performed to assess determinants of intervention use. In total, 1419 participants completed the baseline questionnaire (follow-up response=71.53%, 1015/1419). Intervention use declined rapidly over time; the first 2 intervention sessions were completed by approximately half of the participants and only 10.9% (104/956) of the study population completed all 6 sessions of the intervention. There were no significant differences in use between the video and text version. Intervention use was significantly higher among participants who were allocated to an

  5. A video, text, and speech-driven realistic 3-d virtual head for human-machine interface.

    Science.gov (United States)

    Yu, Jun; Wang, Zeng-Fu

    2015-05-01

    A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facial animation. The online appearance model is used to track 3-D facial motion from video in the framework of particle filtering, and multiple measurements, i.e., pixel color value of input image and Gabor wavelet coefficient of illumination ratio image, are infused to reduce the influence of lighting and person dependence for the construction of online appearance model. The tri-phone model is used to reduce the computational consumption of visual co-articulation in speech synchronized viseme synthesis without sacrificing any performance. The objective and subjective experiments show that the system is suitable for human-machine interaction.

  6. Extracting Various Classes of Data From Biological Text Using the Concept of Existence Dependency.

    Science.gov (United States)

    Taha, Kamal

    2015-11-01

    One of the key goals of biological natural language processing (NLP) is the automatic information extraction from biomedical publications. Most current constituency and dependency parsers overlook the semantic relationships between the constituents comprising a sentence and may not be well suited for capturing complex long-distance dependences. We propose in this paper a hybrid constituency-dependency parser for biological NLP information extraction called EDCC. EDCC aims at enhancing the state of the art of biological text mining by applying novel linguistic computational techniques that overcome the limitations of current constituency and dependency parsers outlined earlier, as follows: 1) it determines the semantic relationship between each pair of constituents in a sentence using novel semantic rules; and 2) it applies a semantic relationship extraction model that extracts information from different structural forms of constituents in sentences. EDCC can be used to extract different types of data from biological texts for purposes such as protein function prediction, genetic network construction, and protein-protein interaction detection. We evaluated the quality of EDCC by comparing it experimentally with six systems. Results showed marked improvement.

  7. Vaccine adverse event text mining system for extracting features from vaccine safety reports.

    Science.gov (United States)

    Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

    2012-01-01

    To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

  8. Large-scale extraction of gene interactions from full-text literature using DeepDive.

    Science.gov (United States)

    Mallory, Emily K; Zhang, Ce; Ré, Christopher; Altman, Russ B

    2016-01-01

    A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles. We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles. Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app russ.altman@stanford.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  9. Challenges for automatically extracting molecular interactions from full-text articles.

    Science.gov (United States)

    McIntosh, Tara; Curran, James R

    2009-09-24

    The increasing availability of full-text biomedical articles will allow more biomedical knowledge to be extracted automatically with greater reliability. However, most Information Retrieval (IR) and Extraction (IE) tools currently process only abstracts. The lack of corpora has limited the development of tools that are capable of exploiting the knowledge in full-text articles. As a result, there has been little investigation into the advantages of full-text document structure, and the challenges developers will face in processing full-text articles. We manually annotated passages from full-text articles that describe interactions summarised in a Molecular Interaction Map (MIM). Our corpus tracks the process of identifying facts to form the MIM summaries and captures any factual dependencies that must be resolved to extract the fact completely. For example, a fact in the results section may require a synonym defined in the introduction. The passages are also annotated with negated and coreference expressions that must be resolved.We describe the guidelines for identifying relevant passages and possible dependencies. The corpus includes 2162 sentences from 78 full-text articles. Our corpus analysis demonstrates the necessity of full-text processing; identifies the article sections where interactions are most commonly stated; and quantifies the proportion of interaction statements requiring coherent dependencies. Further, it allows us to report on the relative importance of identifying synonyms and resolving negated expressions. We also experiment with an oracle sentence retrieval system using the corpus as a gold-standard evaluation set. We introduce the MIM corpus, a unique resource that maps interaction facts in a MIM to annotated passages within full-text articles. It is an invaluable case study providing guidance to developers of biomedical IR and IE systems, and can be used as a gold-standard evaluation set for full-text IR tasks.

  10. The Fractal Patterns of Words in a Text: A Method for Automatic Keyword Extraction.

    Science.gov (United States)

    Najafi, Elham; Darooneh, Amir H

    2015-01-01

    A text can be considered as a one dimensional array of words. The locations of each word type in this array form a fractal pattern with certain fractal dimension. We observe that important words responsible for conveying the meaning of a text have dimensions considerably different from one, while the fractal dimensions of unimportant words are close to one. We introduce an index quantifying the importance of the words in a given text using their fractal dimensions and then ranking them according to their importance. This index measures the difference between the fractal pattern of a word in the original text relative to a shuffled version. Because the shuffled text is meaningless (i.e., words have no importance), the difference between the original and shuffled text can be used to ascertain degree of fractality. The degree of fractality may be used for automatic keyword detection. Words with the degree of fractality higher than a threshold value are assumed to be the retrieved keywords of the text. We measure the efficiency of our method for keywords extraction, making a comparison between our proposed method and two other well-known methods of automatic keyword extraction.

  11. The Fractal Patterns of Words in a Text: A Method for Automatic Keyword Extraction

    Science.gov (United States)

    Najafi, Elham; Darooneh, Amir H.

    2015-01-01

    A text can be considered as a one dimensional array of words. The locations of each word type in this array form a fractal pattern with certain fractal dimension. We observe that important words responsible for conveying the meaning of a text have dimensions considerably different from one, while the fractal dimensions of unimportant words are close to one. We introduce an index quantifying the importance of the words in a given text using their fractal dimensions and then ranking them according to their importance. This index measures the difference between the fractal pattern of a word in the original text relative to a shuffled version. Because the shuffled text is meaningless (i.e., words have no importance), the difference between the original and shuffled text can be used to ascertain degree of fractality. The degree of fractality may be used for automatic keyword detection. Words with the degree of fractality higher than a threshold value are assumed to be the retrieved keywords of the text. We measure the efficiency of our method for keywords extraction, making a comparison between our proposed method and two other well-known methods of automatic keyword extraction. PMID:26091207

  12. Valx: A System for Extracting and Structuring Numeric Lab Test Comparison Statements from Text.

    Science.gov (United States)

    Hao, Tianyong; Liu, Hongfang; Weng, Chunhua

    2016-05-17

    To develop an automated method for extracting and structuring numeric lab test comparison statements from text and evaluate the method using clinical trial eligibility criteria text. Leveraging semantic knowledge from the Unified Medical Language System (UMLS) and domain knowledge acquired from the Internet, Valx takes seven steps to extract and normalize numeric lab test expressions: 1) text preprocessing, 2) numeric, unit, and comparison operator extraction, 3) variable identification using hybrid knowledge, 4) variable - numeric association, 5) context-based association filtering, 6) measurement unit normalization, and 7) heuristic rule-based comparison statements verification. Our reference standard was the consensus-based annotation among three raters for all comparison statements for two variables, i.e., HbA1c and glucose, identified from all of Type 1 and Type 2 diabetes trials in ClinicalTrials.gov. The precision, recall, and F-measure for structuring HbA1c comparison statements were 99.6%, 98.1%, 98.8% for Type 1 diabetes trials, and 98.8%, 96.9%, 97.8% for Type 2 diabetes trials, respectively. The precision, recall, and F-measure for structuring glucose comparison statements were 97.3%, 94.8%, 96.1% for Type 1 diabetes trials, and 92.3%, 92.3%, 92.3% for Type 2 diabetes trials, respectively. Valx is effective at extracting and structuring free-text lab test comparison statements in clinical trial summaries. Future studies are warranted to test its generalizability beyond eligibility criteria text. The open-source Valx enables its further evaluation and continued improvement among the collaborative scientific community.

  13. Automatic extraction of property norm-like data from large text corpora.

    Science.gov (United States)

    Kelly, Colin; Devereux, Barry; Korhonen, Anna

    2014-01-01

    Traditional methods for deriving property-based representations of concepts from text have focused on either extracting only a subset of possible relation types, such as hyponymy/hypernymy (e.g., car is-a vehicle) or meronymy/metonymy (e.g., car has wheels), or unspecified relations (e.g., car--petrol). We propose a system for the challenging task of automatic, large-scale acquisition of unconstrained, human-like property norms from large text corpora, and discuss the theoretical implications of such a system. We employ syntactic, semantic, and encyclopedic information to guide our extraction, yielding concept-relation-feature triples (e.g., car be fast, car require petrol, car cause pollution), which approximate property-based conceptual representations. Our novel method extracts candidate triples from parsed corpora (Wikipedia and the British National Corpus) using syntactically and grammatically motivated rules, then reweights triples with a linear combination of their frequency and four statistical metrics. We assess our system output in three ways: lexical comparison with norms derived from human-generated property norm data, direct evaluation by four human judges, and a semantic distance comparison with both WordNet similarity data and human-judged concept similarity ratings. Our system offers a viable and performant method of plausible triple extraction: Our lexical comparison shows comparable performance to the current state-of-the-art, while subsequent evaluations exhibit the human-like character of our generated properties.

  14. Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

    Science.gov (United States)

    Liang, Yu-Li

    Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

  15. Building a protein name dictionary from full text: a machine learning term extraction approach

    Directory of Open Access Journals (Sweden)

    Campagne Fabien

    2005-04-01

    Full Text Available Abstract Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. Results We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. Conclusion This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt.

  16. DiMeX: A Text Mining System for Mutation-Disease Association Extraction.

    Science.gov (United States)

    Mahmood, A S M Ashique; Wu, Tsung-Jung; Mazumder, Raja; Vijay-Shanker, K

    2016-01-01

    The number of published articles describing associations between mutations and diseases is increasing at a fast pace. There is a pressing need to gather such mutation-disease associations into public knowledge bases, but manual curation slows down the growth of such databases. We have addressed this problem by developing a text-mining system (DiMeX) to extract mutation to disease associations from publication abstracts. DiMeX consists of a series of natural language processing modules that preprocess input text and apply syntactic and semantic patterns to extract mutation-disease associations. DiMeX achieves high precision and recall with F-scores of 0.88, 0.91 and 0.89 when evaluated on three different datasets for mutation-disease associations. DiMeX includes a separate component that extracts mutation mentions in text and associates them with genes. This component has been also evaluated on different datasets and shown to achieve state-of-the-art performance. The results indicate that our system outperforms the existing mutation-disease association tools, addressing the low precision problems suffered by most approaches. DiMeX was applied on a large set of abstracts from Medline to extract mutation-disease associations, as well as other relevant information including patient/cohort size and population data. The results are stored in a database that can be queried and downloaded at http://biotm.cis.udel.edu/dimex/. We conclude that this high-throughput text-mining approach has the potential to significantly assist researchers and curators to enrich mutation databases.

  17. Lane Detection in Video-Based Intelligent Transportation Monitoring via Fast Extracting and Clustering of Vehicle Motion Trajectories

    Directory of Open Access Journals (Sweden)

    Jianqiang Ren

    2014-01-01

    Full Text Available Lane detection is a crucial process in video-based transportation monitoring system. This paper proposes a novel method to detect the lane center via rapid extraction and high accuracy clustering of vehicle motion trajectories. First, we use the activity map to realize automatically the extraction of road region, the calibration of dynamic camera, and the setting of three virtual detecting lines. Secondly, the three virtual detecting lines and a local background model with traffic flow feedback are used to extract and group vehicle feature points in unit of vehicle. Then, the feature point groups are described accurately by edge weighted dynamic graph and modified by a motion-similarity Kalman filter during the sparse feature point tracking. After obtaining the vehicle trajectories, a rough k-means incremental clustering with Hausdorff distance is designed to realize the rapid online extraction of lane center with high accuracy. The use of rough set reduces effectively the accuracy decrease, which results from the trajectories that run irregularly. Experimental results prove that the proposed method can detect lane center position efficiently, the affected time of subsequent tasks can be reduced obviously, and the safety of traffic surveillance systems can be enhanced significantly.

  18. Extracting and connecting chemical structures from text sources using chemicalize.org.

    Science.gov (United States)

    Southan, Christopher; Stracz, Andras

    2013-04-23

    Exploring bioactive chemistry requires navigating between structures and data from a variety of text-based sources. While PubChem currently includes approximately 16 million document-extracted structures (15 million from patents) the extent of public inter-document and document-to-database links is still well below any estimated total, especially for journal articles. A major expansion in access to text-entombed chemistry is enabled by chemicalize.org. This on-line resource can process IUPAC names, SMILES, InChI strings, CAS numbers and drug names from pasted text, PDFs or URLs to generate structures, calculate properties and launch searches. Here, we explore its utility for answering questions related to chemical structures in documents and where these overlap with database records. These aspects are illustrated using a common theme of Dipeptidyl Peptidase 4 (DPPIV) inhibitors. Full-text open URL sources facilitated the download of over 1400 structures from a DPPIV patent and the alignment of specific examples with IC50 data. Uploading the SMILES to PubChem revealed extensive linking to patents and papers, including prior submissions from chemicalize.org as submitting source. A DPPIV medicinal chemistry paper was completely extracted and structures were aligned to the activity results table, as well as linked to other documents via PubChem. In both cases, key structures with data were partitioned from common chemistry by dividing them into individual new PDFs for conversion. Over 500 structures were also extracted from a batch of PubMed abstracts related to DPPIV inhibition. The drug structures could be stepped through each text occurrence and included some converted MeSH-only IUPAC names not linked in PubChem. Performing set intersections proved effective for detecting compounds-in-common between documents and merged extractions. This work demonstrates the utility of chemicalize.org for the exploration of chemical structure connectivity between documents and

  19. Understanding disciplinary vocabularies using a full-text enabled domain-independent term extraction approach.

    Science.gov (United States)

    Yan, Erjia; Williams, Jake; Chen, Zheng

    2017-01-01

    Publication metadata help deliver rich analyses of scholarly communication. However, research concepts and ideas are more effectively expressed through unstructured fields such as full texts. Thus, the goals of this paper are to employ a full-text enabled method to extract terms relevant to disciplinary vocabularies, and through them, to understand the relationships between disciplines. This paper uses an efficient, domain-independent term extraction method to extract disciplinary vocabularies from a large multidisciplinary corpus of PLoS ONE publications. It finds a power-law pattern in the frequency distributions of terms present in each discipline, indicating a semantic richness potentially sufficient for further study and advanced analysis. The salient relationships amongst these vocabularies become apparent in application of a principal component analysis. For example, Mathematics and Computer and Information Sciences were found to have similar vocabulary use patterns along with Engineering and Physics; while Chemistry and the Social Sciences were found to exhibit contrasting vocabulary use patterns along with the Earth Sciences and Chemistry. These results have implications to studies of scholarly communication as scholars attempt to identify the epistemological cultures of disciplines, and as a full text-based methodology could lead to machine learning applications in the automated classification of scholarly work according to disciplinary vocabularies.

  20. Improving the extraction of complex regulatory events from scientific text by using ontology-based inference

    Directory of Open Access Journals (Sweden)

    Kim Jung-jae

    2011-10-01

    Full Text Available Abstract Background The extraction of complex events from biomedical text is a challenging task and requires in-depth semantic analysis. Previous approaches associate lexical and syntactic resources with ontologies for the semantic analysis, but fall short in testing the benefits from the use of domain knowledge. Results We developed a system that deduces implicit events from explicitly expressed events by using inference rules that encode domain knowledge. We evaluated the system with the inference module on three tasks: First, when tested against a corpus with manually annotated events, the inference module of our system contributes 53.2% of correct extractions, but does not cause any incorrect results. Second, the system overall reproduces 33.1% of the transcription regulatory events contained in RegulonDB (up to 85.0% precision and the inference module is required for 93.8% of the reproduced events. Third, we applied the system with minimum adaptations to the identification of cell activity regulation events, confirming that the inference improves the performance of the system also on this task. Conclusions Our research shows that the inference based on domain knowledge plays a significant role in extracting complex events from text. This approach has great potential in recognizing the complex concepts of such biomedical ontologies as Gene Ontology in the literature.

  1. COMPOSITIONAL AND CONTENT-RELATED PARTICULARITIES OF POLITICAL MEDIA TEXTS (THROUGH THE EXAMPLE OF THE TEXTS OF POLITICAL VIDEO CLIPS ISSUED BY THE CANDIDATES FOR PRESIDENCY IN FRANCE IN 2017

    Directory of Open Access Journals (Sweden)

    Dmitrieva, A.V.

    2017-09-01

    Full Text Available The article examines the texts of political advertising video clips issued by the candidates for presidency in France during the campaign before the first round of elections in 2017. The mentioned examples of media texts are analysed from the compositional point of view as well as from that of the content particularities which are directly connected to the text structure. In general, the majority of the studied clips have a similar structure and consist of three parts: introduction, main part and conclusion. However, as a result of the research, a range of advantages marking well-structured videos was revealed. These include: addressing the voters and stating the speech topic clearly at the beginning of the clip, a relevant attention-grabbing opening phrase, consistency and clarity of the information presentation, appropriate use of additional video plots, conclusion at the end of the clip.

  2. Medical Student and Tutor Perceptions of Video Versus Text in an Interactive Online Virtual Patient for Problem-Based Learning: A Pilot Study

    Science.gov (United States)

    Ellaway, Rachel H; Round, Jonathan; Vaughan, Sophie; Poulton, Terry; Zary, Nabil

    2015-01-01

    Background The impact of the use of video resources in primarily paper-based problem-based learning (PBL) settings has been widely explored. Although it can provide many benefits, the use of video can also hamper the critical thinking of learners in contexts where learners are developing clinical reasoning. However, the use of video has not been explored in the context of interactive virtual patients for PBL. Objective A pilot study was conducted to explore how undergraduate medical students interpreted and evaluated information from video- and text-based materials presented in the context of a branched interactive online virtual patient designed for PBL. The goal was to inform the development and use of virtual patients for PBL and to inform future research in this area. Methods An existing virtual patient for PBL was adapted for use in video and provided as an intervention to students in the transition year of the undergraduate medicine course at St George’s, University of London. Survey instruments were used to capture student and PBL tutor experiences and perceptions of the intervention, and a formative review meeting was run with PBL tutors. Descriptive statistics were generated for the structured responses and a thematic analysis was used to identify emergent themes in the unstructured responses. Results Analysis of student responses (n=119) and tutor comments (n=18) yielded 8 distinct themes relating to the perceived educational efficacy of information presented in video and text formats in a PBL context. Although some students found some characteristics of the videos beneficial, when asked to express a preference for video or text the majority of those that responded to the question (65%, 65/100) expressed a preference for text. Student responses indicated that the use of video slowed the pace of PBL and impeded students’ ability to review and critically appraise the presented information. Conclusions Our findings suggest that text was perceived to be a

  3. Medical Student and Tutor Perceptions of Video Versus Text in an Interactive Online Virtual Patient for Problem-Based Learning: A Pilot Study.

    Science.gov (United States)

    Woodham, Luke A; Ellaway, Rachel H; Round, Jonathan; Vaughan, Sophie; Poulton, Terry; Zary, Nabil

    2015-06-18

    The impact of the use of video resources in primarily paper-based problem-based learning (PBL) settings has been widely explored. Although it can provide many benefits, the use of video can also hamper the critical thinking of learners in contexts where learners are developing clinical reasoning. However, the use of video has not been explored in the context of interactive virtual patients for PBL. A pilot study was conducted to explore how undergraduate medical students interpreted and evaluated information from video- and text-based materials presented in the context of a branched interactive online virtual patient designed for PBL. The goal was to inform the development and use of virtual patients for PBL and to inform future research in this area. An existing virtual patient for PBL was adapted for use in video and provided as an intervention to students in the transition year of the undergraduate medicine course at St George's, University of London. Survey instruments were used to capture student and PBL tutor experiences and perceptions of the intervention, and a formative review meeting was run with PBL tutors. Descriptive statistics were generated for the structured responses and a thematic analysis was used to identify emergent themes in the unstructured responses. Analysis of student responses (n=119) and tutor comments (n=18) yielded 8 distinct themes relating to the perceived educational efficacy of information presented in video and text formats in a PBL context. Although some students found some characteristics of the videos beneficial, when asked to express a preference for video or text the majority of those that responded to the question (65%, 65/100) expressed a preference for text. Student responses indicated that the use of video slowed the pace of PBL and impeded students' ability to review and critically appraise the presented information. Our findings suggest that text was perceived to be a better source of information than video in virtual

  4. Effectiveness of a Video-Versus Text-Based Computer-Tailored Intervention for Obesity Prevention after One Year: A Randomized Controlled Trial

    Directory of Open Access Journals (Sweden)

    Kei Long Cheung

    2017-10-01

    Full Text Available Computer-tailored programs may help to prevent overweight and obesity, which are worldwide public health problems. This study investigated (1 the 12-month effectiveness of a video- and text-based computer-tailored intervention on energy intake, physical activity, and body mass index (BMI, and (2 the role of educational level in intervention effects. A randomized controlled trial in The Netherlands was conducted, in which adults were allocated to a video-based condition, text-based condition, or control condition, with baseline, 6 months, and 12 months follow-up. Outcome variables were self-reported BMI, physical activity, and energy intake. Mixed-effects modelling was used to investigate intervention effects and potential interaction effects. Compared to the control group, the video intervention group was effective regarding energy intake after 6 months (least squares means (LSM difference = −205.40, p = 0.00 and 12 months (LSM difference = −128.14, p = 0.03. Only video intervention resulted in lower average daily energy intake after one year (d = 0.12. Educational role and BMI did not seem to interact with this effect. No intervention effects on BMI and physical activity were found. The video computer-tailored intervention was effective on energy intake after one year. This effect was not dependent on educational levels or BMI categories, suggesting that video tailoring can be effective for a broad range of risk groups and may be preferred over text tailoring.

  5. Improving the extraction of complex regulatory events from scientific text by using ontology-based inference.

    Science.gov (United States)

    Kim, Jung-Jae; Rebholz-Schuhmann, Dietrich

    2011-10-06

    The extraction of complex events from biomedical text is a challenging task and requires in-depth semantic analysis. Previous approaches associate lexical and syntactic resources with ontologies for the semantic analysis, but fall short in testing the benefits from the use of domain knowledge. We developed a system that deduces implicit events from explicitly expressed events by using inference rules that encode domain knowledge. We evaluated the system with the inference module on three tasks: First, when tested against a corpus with manually annotated events, the inference module of our system contributes 53.2% of correct extractions, but does not cause any incorrect results. Second, the system overall reproduces 33.1% of the transcription regulatory events contained in RegulonDB (up to 85.0% precision) and the inference module is required for 93.8% of the reproduced events. Third, we applied the system with minimum adaptations to the identification of cell activity regulation events, confirming that the inference improves the performance of the system also on this task. Our research shows that the inference based on domain knowledge plays a significant role in extracting complex events from text. This approach has great potential in recognizing the complex concepts of such biomedical ontologies as Gene Ontology in the literature.

  6. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

    Science.gov (United States)

    Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

    2013-01-01

    Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

  7. Interdisciplinary Approach to the Mental Lexicon: Neural Network and Text Extraction From Long-term Memory

    Directory of Open Access Journals (Sweden)

    Vardan G. Arutyunyan

    2013-01-01

    Full Text Available The paper touches upon the principles of mental lexicon organization in the light of recent research in psycho- and neurolinguistics. As a focal point of discussion two main approaches to mental lexicon functioning are considered: modular or dual-system approach, developed within generativism and opposite single-system approach, representatives of which are the connectionists and supporters of network models. The paper is an endeavor towards advocating the viewpoint that mental lexicon is complex psychological organization based upon specific composition of neural network. In this regard, the paper further elaborates on the matter of storing text in human mental space and introduces a model of text extraction from long-term memory. Based upon data available, the author develops a methodology of modeling structures of knowledge representation in the systems of artificial intelligence.

  8. Towards A Model Of Knowledge Extraction Of Text Mining For Palliative Care Patients In Panama.

    Directory of Open Access Journals (Sweden)

    Denis Cedeno Moreno

    2015-08-01

    Full Text Available Solutions using information technology is an innovative way to manage the information hospice patients in hospitals in Panama. The application of techniques of text mining for the domain of medicine especially information from electronic health records of patients in palliative care is one of the most recent and promising research areas for the analysis of textual data. Text mining is based on new knowledge extraction from unstructured natural language data. We may also create ontologies to describe the terminology and knowledge in a given domain. In an ontology conceptualization of a domain that may be general or specific formalized. Knowledge can be used for decision making by health specialists or can help in research topics for improving the health system.

  9. Effectiveness of a Video-Versus Text-Based Computer-Tailored Intervention for Obesity Prevention after One Year: A Randomized Controlled Trial

    Science.gov (United States)

    Cheung, Kei Long; Schwabe, Inga; Walthouwer, Michel J. L.; Oenema, Anke; de Vries, Hein

    2017-01-01

    Computer-tailored programs may help to prevent overweight and obesity, which are worldwide public health problems. This study investigated (1) the 12-month effectiveness of a video- and text-based computer-tailored intervention on energy intake, physical activity, and body mass index (BMI), and (2) the role of educational level in intervention effects. A randomized controlled trial in The Netherlands was conducted, in which adults were allocated to a video-based condition, text-based condition, or control condition, with baseline, 6 months, and 12 months follow-up. Outcome variables were self-reported BMI, physical activity, and energy intake. Mixed-effects modelling was used to investigate intervention effects and potential interaction effects. Compared to the control group, the video intervention group was effective regarding energy intake after 6 months (least squares means (LSM) difference = −205.40, p = 0.00) and 12 months (LSM difference = −128.14, p = 0.03). Only video intervention resulted in lower average daily energy intake after one year (d = 0.12). Educational role and BMI did not seem to interact with this effect. No intervention effects on BMI and physical activity were found. The video computer-tailored intervention was effective on energy intake after one year. This effect was not dependent on educational levels or BMI categories, suggesting that video tailoring can be effective for a broad range of risk groups and may be preferred over text tailoring. PMID:29065545

  10. A crowdsourcing workflow for extracting chemical-induced disease relations from free text

    Science.gov (United States)

    Li, Tong Shu; Bravo, Àlex; Furlong, Laura I.; Good, Benjamin M.; Su, Andrew I.

    2016-01-01

    Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505 F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available at https://github.com/SuLab/crowd_cid_relex Database URL: https://github.com/SuLab/crowd_cid_relex PMID:27087308

  11. EnvMine: A text-mining system for the automatic extraction of contextual information

    Directory of Open Access Journals (Sweden)

    de Lorenzo Victor

    2010-06-01

    Full Text Available Abstract Background For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles. So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations from textual sources of any kind. Results EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings. Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude, thus allowing the calculation of distance between the individual locations. Conclusion EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical

  12. Overview of image processing tools to extract physical information from JET videos

    Science.gov (United States)

    Craciunescu, T.; Murari, A.; Gelfusa, M.; Tiseanu, I.; Zoita, V.; EFDA Contributors, JET

    2014-11-01

    In magnetic confinement nuclear fusion devices such as JET, the last few years have witnessed a significant increase in the use of digital imagery, not only for the surveying and control of experiments, but also for the physical interpretation of results. More than 25 cameras are routinely used for imaging on JET in the infrared (IR) and visible spectral regions. These cameras can produce up to tens of Gbytes per shot and their information content can be very different, depending on the experimental conditions. However, the relevant information about the underlying physical processes is generally of much reduced dimensionality compared to the recorded data. The extraction of this information, which allows full exploitation of these diagnostics, is a challenging task. The image analysis consists, in most cases, of inverse problems which are typically ill-posed mathematically. The typology of objects to be analysed is very wide, and usually the images are affected by noise, low levels of contrast, low grey-level in-depth resolution, reshaping of moving objects, etc. Moreover, the plasma events have time constants of ms or tens of ms, which imposes tough conditions for real-time applications. On JET, in the last few years new tools and methods have been developed for physical information retrieval. The methodology of optical flow has allowed, under certain assumptions, the derivation of information about the dynamics of video objects associated with different physical phenomena, such as instabilities, pellets and filaments. The approach has been extended in order to approximate the optical flow within the MPEG compressed domain, allowing the manipulation of the large JET video databases and, in specific cases, even real-time data processing. The fast visible camera may provide new information that is potentially useful for disruption prediction. A set of methods, based on the extraction of structural information from the visual scene, have been developed for the

  13. Overview of image processing tools to extract physical information from JET videos

    International Nuclear Information System (INIS)

    Craciunescu, T; Tiseanu, I; Zoita, V; Murari, A; Gelfusa, M

    2014-01-01

    In magnetic confinement nuclear fusion devices such as JET, the last few years have witnessed a significant increase in the use of digital imagery, not only for the surveying and control of experiments, but also for the physical interpretation of results. More than 25 cameras are routinely used for imaging on JET in the infrared (IR) and visible spectral regions. These cameras can produce up to tens of Gbytes per shot and their information content can be very different, depending on the experimental conditions. However, the relevant information about the underlying physical processes is generally of much reduced dimensionality compared to the recorded data. The extraction of this information, which allows full exploitation of these diagnostics, is a challenging task. The image analysis consists, in most cases, of inverse problems which are typically ill-posed mathematically. The typology of objects to be analysed is very wide, and usually the images are affected by noise, low levels of contrast, low grey-level in-depth resolution, reshaping of moving objects, etc. Moreover, the plasma events have time constants of ms or tens of ms, which imposes tough conditions for real-time applications. On JET, in the last few years new tools and methods have been developed for physical information retrieval. The methodology of optical flow has allowed, under certain assumptions, the derivation of information about the dynamics of video objects associated with different physical phenomena, such as instabilities, pellets and filaments. The approach has been extended in order to approximate the optical flow within the MPEG compressed domain, allowing the manipulation of the large JET video databases and, in specific cases, even real-time data processing. The fast visible camera may provide new information that is potentially useful for disruption prediction. A set of methods, based on the extraction of structural information from the visual scene, have been developed for the

  14. A method for extracting design rationale knowledge based on Text Mining

    Directory of Open Access Journals (Sweden)

    Liu Jihong

    2017-01-01

    Full Text Available Capture design rationale (DR knowledge and presenting it to designers by good form, which have great significance for design reuse and design innovation. Since the 1970s design rationality began to develop, many teams have developed their own design rational system. However, the DR acquisition system is not intelligent enough, and it still requires designers to do a lot of operations. In addition, the existing design documents contain a large number of DR knowledge, but it has not been well excavated. Therefore, a method and system are needed to better extract DR knowledge in design documents. We have proposed a DRKH (design rationale knowledge hierarchy model for DR representation. The DRKH model has three layers, respectively as design intent layer, design decision layer and design basis layer. In this paper, we use text mining method to extract DR from design documents and construct DR model. Finally, the welding robot design specification is taken as an example to demonstrate the system interface.

  15. A crowdsourcing workflow for extracting chemical-induced disease relations from free text.

    Science.gov (United States)

    Li, Tong Shu; Bravo, Àlex; Furlong, Laura I; Good, Benjamin M; Su, Andrew I

    2016-01-01

    Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available athttps://github.com/SuLab/crowd_cid_relexDatabase URL:https://github.com/SuLab/crowd_cid_relex. © The Author(s) 2016. Published by Oxford University Press.

  16. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2017-03-01

    Full Text Available Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT, speed-up robust feature (SURF, local binary patterns (LBP, histogram of oriented gradients (HOG, and weighted HOG. Recently, the convolutional neural network (CNN method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  17. Efficient Foreground Extraction From HEVC Compressed Video for Application to Real-Time Analysis of Surveillance 'Big' Data.

    Science.gov (United States)

    Dey, Bhaskar; Kundu, Malay K

    2015-11-01

    While surveillance video is the biggest source of unstructured Big Data today, the emergence of high-efficiency video coding (HEVC) standard is poised to have a huge role in lowering the costs associated with transmission and storage. Among the benefits of HEVC over the legacy MPEG-4 Advanced Video Coding (AVC), is a staggering 40 percent or more bitrate reduction at the same visual quality. Given the bandwidth limitations, video data are compressed essentially by removing spatial and temporal correlations that exist in its uncompressed form. This causes compressed data, which are already de-correlated, to serve as a vital resource for machine learning with significantly fewer samples for training. In this paper, an efficient approach to foreground extraction/segmentation is proposed using novel spatio-temporal de-correlated block features extracted directly from the HEVC compressed video. Most related techniques, in contrast, work on uncompressed images claiming significant storage and computational resources not only for the decoding process prior to initialization but also for the feature selection/extraction and background modeling stage following it. The proposed approach has been qualitatively and quantitatively evaluated against several other state-of-the-art methods.

  18. Clinical records anonymisation and text extraction (CRATE): an open-source software system.

    Science.gov (United States)

    Cardinal, Rudolf N

    2017-04-26

    Electronic medical records contain information of value for research, but contain identifiable and often highly sensitive confidential information. Patient-identifiable information cannot in general be shared outside clinical care teams without explicit consent, but anonymisation/de-identification allows research uses of clinical data without explicit consent. This article presents CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system with separable functions: (1) it anonymises or de-identifies arbitrary relational databases, with sensitivity and precision similar to previous comparable systems; (2) it uses public secure cryptographic methods to map patient identifiers to research identifiers (pseudonyms); (3) it connects relational databases to external tools for natural language processing; (4) it provides a web front end for research and administrative functions; and (5) it supports a specific model through which patients may consent to be contacted about research. Creation and management of a research database from sensitive clinical records with secure pseudonym generation, full-text indexing, and a consent-to-contact process is possible and practical using entirely free and open-source software.

  19. A methodology for semiautomatic taxonomy of concepts extraction from nuclear scientific documents using text mining techniques

    International Nuclear Information System (INIS)

    Braga, Fabiane dos Reis

    2013-01-01

    This thesis presents a text mining method for semi-automatic extraction of taxonomy of concepts, from a textual corpus composed of scientific papers related to nuclear area. The text classification is a natural human practice and a crucial task for work with large repositories. The document clustering technique provides a logical and understandable framework that facilitates the organization, browsing and searching. Most clustering algorithms using the bag of words model to represent the content of a document. This model generates a high dimensionality of the data, ignores the fact that different words can have the same meaning and does not consider the relationship between them, assuming that words are independent of each other. The methodology presents a combination of a model for document representation by concepts with a hierarchical document clustering method using frequency of co-occurrence concepts and a technique for clusters labeling more representatives, with the objective of producing a taxonomy of concepts which may reflect a structure of the knowledge domain. It is hoped that this work will contribute to the conceptual mapping of scientific production of nuclear area and thus support the management of research activities in this area. (author)

  20. Extraction of events and rules of land use/cover change from the policy text

    Science.gov (United States)

    Lin, Guangfa; Xia, Beicheng; Huang, Wangli; Jiang, Huixian; Chen, Youfei

    2007-06-01

    The database of recording the snapshots of land parcels history is the foundation for the most of the models on simulating land use/cover change (LUCC) process. But the sequences of temporal snapshots are not sufficient to deduce and describe the mechanism of LUCC process. The temporal relationship between scenarios of LUCC we recorded could not be transfer into causal relationship categorically, which was regarded as a key factor in spatial-temporal reasoning. The proprietor of land parcels adapted themselves to the policies from governments and the change of production market, and then made decisions in this or that way. The occurrence of each change of a land parcel in an urban area was often related with one or more decision texts when it was investigated on the local scale with high resolution of the background scene. These decision texts may come from different sections of a hierarchical government system on different levels, such as villages or communities, towns or counties, cities, provinces or even the paramount. All these texts were balance results between advantages and disadvantages of different interest groups. They are the essential forces of LUCC in human dimension. Up to now, a methodology is still wanted for on how to express these forces in a simulation system using GIS as a language. The presented paper was part of our initial research on this topic. The term "Event" is a very important concept in the frame of "Object-Oriented" theory in computer science. While in the domain of temporal GIS, the concept of event was developed in another category. The definitions of the event and their transformation relationship were discussed in this paper on three modeling levels as real world level, conceptual level and programming level. In this context, with a case study of LUCC in recent 30 years in Xiamen city of Fujian province, P. R. China, the paper focused on how to extract information of events and rules from the policy files collected and integrate

  1. Learners' Use of Communication Strategies in Text-Based and Video-Based Synchronous Computer-Mediated Communication Environments: Opportunities for Language Learning

    Science.gov (United States)

    Hung, Yu-Wan; Higgins, Steve

    2016-01-01

    This study investigates the different learning opportunities enabled by text-based and video-based synchronous computer-mediated communication (SCMC) from an interactionist perspective. Six Chinese-speaking learners of English and six English-speaking learners of Chinese were paired up as tandem (reciprocal) learning dyads. Each dyad participated…

  2. Pregnancy Prevention at Her Fingertips: A Text- and Mobile Video-Based Pilot Intervention to Promote Contraceptive Methods among College Women

    Science.gov (United States)

    Walsh-Buhi, Eric R.; Helmy, Hannah; Harsch, Kristin; Rella, Natalie; Godcharles, Cheryl; Ogunrunde, Adejoke; Lopez Castillo, Humberto

    2016-01-01

    Objective: This paper reports on a pilot study evaluating the feasibility and acceptability of a text- and mobile video-based intervention to educate women and men attending college about non-daily contraception, with a particular focus on long-acting reversible contraception (LARC). A secondary objective is to describe the process of intervention…

  3. Efficient extraction of protein-protein interactions from full-text articles.

    Science.gov (United States)

    Hakenberg, Jörg; Leaman, Robert; Vo, Nguyen Ha; Jonnalagadda, Siddhartha; Sullivan, Ryan; Miller, Christopher; Tari, Luis; Baral, Chitta; Gonzalez, Graciela

    2010-01-01

    Proteins and their interactions govern virtually all cellular processes, such as regulation, signaling, metabolism, and structure. Most experimental findings pertaining to such interactions are discussed in research papers, which, in turn, get curated by protein interaction databases. Authors, editors, and publishers benefit from efforts to alleviate the tasks of searching for relevant papers, evidence for physical interactions, and proper identifiers for each protein involved. The BioCreative II.5 community challenge addressed these tasks in a competition-style assessment to evaluate and compare different methodologies, to make aware of the increasing accuracy of automated methods, and to guide future implementations. In this paper, we present our approaches for protein-named entity recognition, including normalization, and for extraction of protein-protein interactions from full text. Our overall goal is to identify efficient individual components, and we compare various compositions to handle a single full-text article in between 10 seconds and 2 minutes. We propose strategies to transfer document-level annotations to the sentence-level, which allows for the creation of a more fine-grained training corpus; we use this corpus to automatically derive around 5,000 patterns. We rank sentences by relevance to the task of finding novel interactions with physical evidence, using a sentence classifier built from this training corpus. Heuristics for paraphrasing sentences help to further remove unnecessary information that might interfere with patterns, such as additional adjectives, clauses, or bracketed expressions. In BioCreative II.5, we achieved an f-score of 22 percent for finding protein interactions, and 43 percent for mapping proteins to UniProt IDs; disregarding species, f-scores are 30 percent and 55 percent, respectively. On average, our best-performing setup required around 2 minutes per full text. All data and pattern sets as well as Java classes that

  4. Text data extraction for a prospective, research-focused data mart: implementation and validation

    Directory of Open Access Journals (Sweden)

    Hinchcliff Monique

    2012-09-01

    Full Text Available Abstract Background Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of ‘machine generated’ sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Methods Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. Results There was a near perfect (99.5% agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Conclusions Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor to parse, abstract and assemble

  5. Improving Students� Ability in Writing Hortatory Exposition Texts by Using Process-Genre Based Approach with YouTube Videos as the Media

    Directory of Open Access Journals (Sweden)

    fifin naili rizkiyah

    2017-06-01

    Full Text Available Abstract: This research is aimed at finding out how Process-Genre Based Approach strategy with YouTube Videos as the media are employed to improve the students� ability in writing hortatory exposition texts. This study uses collaborative classroom action research design following the procedures namely planning, implementing, observing, and reflecting. The procedures of carrying out the strategy are: (1 relating several issues/ cases to the students� background knowledge and introducing the generic structures and linguistic features of hortatory exposition text as the BKoF stage, (2 analyzing the generic structure and the language features used in the text and getting model on how to write a hortatory exposition text by using the YouTube Video as the MoT stage, (3 writing a hortatory exposition text collaboratively in a small group and in pairs through process writing as the JCoT stage, and (4 writing a hortatory exposition text individually as the ICoT stage. The result shows that the use of Process-Genre Based Approach and YouTube Videos can improve the students� ability in writing hortatory exposition texts. The percentage of the students achieving the score above the minimum passing grade (70 had improved from only 15.8% (3 out of 19 students in the preliminary study to 100% (22 students in the Cycle 1. Besides, the score of each aspect; content, organization, vocabulary, grammar, and mechanics also improved. � Key Words: writing ability, hortatory exposition text, process-genre based approach, youtube video

  6. Text data extraction for a prospective, research-focused data mart: implementation and validation.

    Science.gov (United States)

    Hinchcliff, Monique; Just, Eric; Podlusky, Sofia; Varga, John; Chang, Rowland W; Kibbe, Warren A

    2012-09-13

    Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of 'machine generated' sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. There was a near perfect (99.5%) agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor) to parse, abstract and assemble structured data from text data contained in the electronic health

  7. Crowdsourcing step-by-step information extraction to enhance existing how-to videos

    OpenAIRE

    Nguyen, Phu Tran; Weir, Sarah; Guo, Philip J.; Miller, Robert C.; Gajos, Krzysztof Z.; Kim, Ju Ho

    2014-01-01

    Millions of learners today use how-to videos to master new skills in a variety of domains. But browsing such videos is often tedious and inefficient because video player interfaces are not optimized for the unique step-by-step structure of such videos. This research aims to improve the learning experience of existing how-to videos with step-by-step annotations. We first performed a formative study to verify that annotations are actually useful to learners. We created ToolScape, an interac...

  8. The use of telehealth (text messaging and video communications) in patients with cystic fibrosis: A pilot study.

    Science.gov (United States)

    Gur, Michal; Nir, Vered; Teleshov, Anna; Bar-Yoseph, Ronen; Manor, Eynav; Diab, Gizelle; Bentur, Lea

    2017-05-01

    Background Poor communications between cystic fibrosis (CF) patients and health-care providers may result in gaps in knowledge and misconceptions about medication usage, and can lead to poor adherence. We aimed to assess the feasibility of using WhatsApp and Skype to improve communications. Methods This single-centre pilot study included CF patients who were older than eight years of age assigned to two groups: one without intervention (control group), and one with intervention. Each patient from the intervention group received Skype-based online video chats and WhatsApp messages from members of the multidisciplinary CF team. CF questionnaires, revised (CFQ-R) scores, knowledge and adherence based on CF My Way and patients satisfaction were evaluated before and after three months. Feasibility was assessed by session attendance, acceptability and satisfaction survey. Descriptive analysis and paired and non-paired t-tests were used as applicable. Results Eighteen patients were recruited to this feasibility study (nine in each group). Each intervention group participant had between four and six Skype video chats and received 22-45 WhatsApp messages. In this small study, CFQ-R scores, knowledge, adherence and patient satisfaction were similar in both groups before and after the three-month intervention. Conclusions A telehealth-based approach, using Skype video chats and WhatsApp messages, was feasible and acceptable in this pilot study. A larger and longer multi-centre study is warranted to examine the efficacy of these interventions to improve knowledge, adherence and communication.

  9. Students’ Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video: A Qualitative Study

    DEFF Research Database (Denmark)

    Pedersen, Kamilla; Holdgaard, Martin Møller; Paltved, Charlotte

    2017-01-01

    ' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. METHODS: The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed....... Students taught with video-based patient cases, in contrast, often referred to the patient cases when highlighting new insights, including the importance of patient perspectives when communicating with patients. CONCLUSION: The format of patient cases included in teaching may have a substantial impact...... unintended stigma and influence an authoritative approach in medical students towards managing patients in clinical psychiatry....

  10. THE COMPARISON OF DESCRIPTIVE TEXT WRITING ABILITY USING YOU TUBE DOWNLOADED VIDEO AND SERIAL PICTURES AT THE STUDENTS’OF SMPN 2 METROACADEMIC YEAR 2012/2013

    Directory of Open Access Journals (Sweden)

    Eka Bayu Pramanca

    2013-10-01

    Full Text Available This research discusses about how two different techniques affect the students’ ability in descriptive text at SMP N 2 Metro. The objectives of this research are (1 to know the difference result of using YouTube Downloaded Video and Serial Pictures media toward students’ writing ability in descriptive text and (2 to know which one is more effective of students’ writing ability in descriptive text instruction between learning by using YouTube Downloaded Video and Serial Pictures media. The implemented method is quantitative research design in that both researchers use true experimental research design. In this research , experimental and control class pre-test and post test are conducted. It is carried out at the first grade of SMP N 2 Metro in academic year 2012/2013. The population in this research is 7 different classes with total number of 224 students. 2 classes of the total population are taken as the samples; VII.1 students in experimental class and VII.2 students  in control class by using cluster random sampling technique.  The instruments of the research are tests, treatment and post-test. The data analyzing procedure uses t-test  and results the following output. The result of ttest is 3,96 and ttable  is 2,06. It means that tcount > ttable with the criterion of ttest is Ha is accepted if tcount  > ttable. So, there is any difference result of students’ writing ability using YouTube Downloaded Video and Serial Pictures Media. However; Youtube Downloaded Video media is more effective media than Serial Pictures media toward students’ writing ability. This research is consistent with the previous result of the studies and thus this technique is  recommended to use in writing instruction especially in descriptive text in order that students may feel fun and enjoy during the  learning process.

  11. Comparing a Video and Text Version of a Web-Based Computer-Tailored Intervention for Obesity Prevention: A Randomized Controlled Trial.

    Science.gov (United States)

    Walthouwer, Michel Jean Louis; Oenema, Anke; Lechner, Lilian; de Vries, Hein

    2015-10-19

    Web-based computer-tailored interventions often suffer from small effect sizes and high drop-out rates, particularly among people with a low level of education. Using videos as a delivery format can possibly improve the effects and attractiveness of these interventions The main aim of this study was to examine the effects of a video and text version of a Web-based computer-tailored obesity prevention intervention on dietary intake, physical activity, and body mass index (BMI) among Dutch adults. A second study aim was to examine differences in appreciation between the video and text version. The final study aim was to examine possible differences in intervention effects and appreciation per educational level. A three-armed randomized controlled trial was conducted with a baseline and 6 months follow-up measurement. The intervention consisted of six sessions, lasting about 15 minutes each. In the video version, the core tailored information was provided by means of videos. In the text version, the same tailored information was provided in text format. Outcome variables were self-reported and included BMI, physical activity, energy intake, and appreciation of the intervention. Multiple imputation was used to replace missing values. The effect analyses were carried out with multiple linear regression analyses and adjusted for confounders. The process evaluation data were analyzed with independent samples t tests. The baseline questionnaire was completed by 1419 participants and the 6 months follow-up measurement by 1015 participants (71.53%). No significant interaction effects of educational level were found on any of the outcome variables. Compared to the control condition, the video version resulted in lower BMI (B=-0.25, P=.049) and lower average daily energy intake from energy-dense food products (B=-175.58, PWeb-based computer-tailored obesity prevention intervention was the most effective intervention and most appreciated. Future research needs to examine if the

  12. Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions (Open Access)

    Science.gov (United States)

    2013-10-03

    fol- low the setup in the literature ([13, 14]), and use 5 (birdfall, cheetah , girl, monkeydog and parachute) of the videos for evaluation (since the...segmentation labeling results of the method, GT is the ground-truth labeling of the video, and F is the (a) Birdfall (b) Cheetah (c) Girl (d) Monkeydog...Video Ours [14] [13] [20] [6] birdfall 155 189 288 252 454 cheetah 633 806 905 1142 1217 girl 1488 1698 1785 1304 1755 monkeydog 365 472 521 563 683

  13. Multimodal Feature Learning for Video Captioning

    Directory of Open Access Journals (Sweden)

    Sujin Lee

    2018-01-01

    Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.

  14. Conversation Thread Extraction and Topic Detection in Text-Based Chat

    National Research Council Canada - National Science Library

    Adams, Paige H

    2008-01-01

    Text-based chat systems are widely used within the Department of Defense, but the standard systems available do not provide robust capabilities for search, information retrieval, or information assurance...

  15. Text analysis of MEDLINE for discovering functional relationships among genes: evaluation of keyword extraction weighting schemes.

    Science.gov (United States)

    Liu, Ying; Navathe, Shamkant B; Pivoshenko, Alex; Dasigi, Venu G; Dingledine, Ray; Ciliax, Brian J

    2006-01-01

    One of the key challenges of microarray studies is to derive biological insights from the gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the functional links among genes. However, the quality of the keyword lists significantly affects the clustering results. We compared two keyword weighting schemes: normalised z-score and term frequency-inverse document frequency (TFIDF). Two gene sets were tested to evaluate the effectiveness of the weighting schemes for keyword extraction for gene clustering. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords outperformed those produced from normalised z-score weighted keywords. The optimised algorithms should be useful for partitioning genes from microarray lists into functionally discrete clusters.

  16. Computerized extraction of information on the quality of diabetes care from free text in electronic patient records of general practitioners

    NARCIS (Netherlands)

    Voorham, Jaco; Denig, Petra

    2007-01-01

    Objective: This study evaluated a computerized method for extracting numeric clinical measurements related to diabetes care from free text in electronic patient records (EPR) of general practitioners. Design and Measurements: Accuracy of this number-oriented approach was compared to manual chart

  17. EXTRACTION OF BENTHIC COVER INFORMATION FROM VIDEO TOWS AND PHOTOGRAPHS USING OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. T. L. Estomata

    2012-07-01

    Full Text Available Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU, which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA, which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78±0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30±6.11% (p-value = 0.0001, α = 0.05.

  18. Ordering Operations in Square Root Extractions, Analyzing Some Early Medieval Sanskrit Mathematical Texts with the Help of Speech Act Theory

    Science.gov (United States)

    Keller, Agathe

    Procedures for extracting square roots written in Sanskrit in two treatises and their commentaries from the fifth to the twelfth centuries are explored with the help of Textology and Speech Act Theory. An analysis of the number and order of the steps presented in these texts is used to show that their aims were not limited to only describing how to carry out the algorithm. The intentions of authors of these Sanskrit mathematical texts are questioned by taking into account the expressivity of relationships established between the world and the text.1

  19. A Text Mining Approach for Extracting Lessons Learned from Project Documentation: An Illustrative Case Study

    Directory of Open Access Journals (Sweden)

    Benjamin Matthies

    2017-12-01

    Full Text Available Lessons learned are important building blocks for continuous learning in project-based organisations. Nonetheless, the practical reality is that lessons learned are often not consistently reused for organisational learning. Two problems are commonly described in this context: the information overload and the lack of procedures and methods for the assessment and implementation of lessons learned. This paper addresses these problems, and appropriate solutions are combined in a systematic lesson learned process. Latent Dirichlet Allocation is presented to solve the first problem. Regarding the second problem, established risk management methods are adapted. The entire lessons learned process will be demonstrated in a practical case study

  20. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... YouTube Videos » NEI YouTube Videos: Amblyopia Listen NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration ... Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: ...

  1. Page segmentation and text extraction from gray-scale images in microfilm format

    Science.gov (United States)

    Yuan, Qing; Tan, Chew Lim

    2000-12-01

    The paper deals with a suitably designed system that is being used to separate textual regions from graphics regions and locate textual data from textured background. We presented a method based on edge detection to automatically locate text in some noise infected grayscale newspaper images with microfilm format. The algorithm first finds the appropriate edges of textual region using Canny edge detector, and then by edge merging it makes use of edge features to do block segmentation and classification, afterwards feature aided connected component analysis was used to group homogeneous textual regions together within the scope of its bounding box. We can obtain an efficient block segmentation with reduced memory size by introducing the TLC. The proposed method has been used to locate text in a group of newspaper images with multiple page layout. Initial results are encouraging, we would expand the experiment data to over 300 microfilm images with different layout structures, promising result is anticipated with corresponding modification on the prototype of former algorithm to make it more robust and suitable to different cases.

  2. Face Recognition and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Swapnil Vitthal Tathe

    2017-07-01

    Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

  3. Video Retrieval Berdasarkan Teks dan Gambar

    Directory of Open Access Journals (Sweden)

    Rahmi Hidayati

    2013-01-01

    Abstract Retrieval video has been used to search a video based on the query entered by user which were text and image. This system could increase the searching ability on video browsing and expected to reduce the video’s retrieval time. The research purposes were designing and creating a software application of retrieval video based on the text and image on the video. The index process for the text is tokenizing, filtering (stopword, stemming. The results of stemming to saved in the text index table. Index process for the image is to create an image color histogram and compute the mean and standard deviation at each primary color red, green and blue (RGB of each image. The results of feature extraction is stored in the image table The process of video retrieval using the query text, images or both. To text query system to process the text query by looking at the text index tables. If there is a text query on the index table system will display information of the video according to the text query. To image query system to process the image query by finding the value of the feature extraction means red, green means, means blue, red standard deviation, standard deviation and standard deviation of blue green. If the value of the six features extracted query image on the index table image will display the video information system according to the query image. To query text and query images, the system will display the video information if the query text and query images have a relationship that is query text and query image has the same film title.   Keywords—  video, index, retrieval, text, image

  4. Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles.

    Science.gov (United States)

    Xu, Rong; Wang, QuanQiu

    2015-06-01

    Targeted anticancer drugs such as imatinib, trastuzumab and erlotinib dramatically improved treatment outcomes in cancer patients, however, these innovative agents are often associated with unexpected side effects. The pathophysiological mechanisms underlying these side effects are not well understood. The availability of a comprehensive knowledge base of side effects associated with targeted anticancer drugs has the potential to illuminate complex pathways underlying toxicities induced by these innovative drugs. While side effect association knowledge for targeted drugs exists in multiple heterogeneous data sources, published full-text oncological articles represent an important source of pivotal, investigational, and even failed trials in a variety of patient populations. In this study, we present an automatic process to extract targeted anticancer drug-associated side effects (drug-SE pairs) from a large number of high profile full-text oncological articles. We downloaded 13,855 full-text articles from the Journal of Oncology (JCO) published between 1983 and 2013. We developed text classification, relationship extraction, signaling filtering, and signal prioritization algorithms to extract drug-SE pairs from downloaded articles. We extracted a total of 26,264 drug-SE pairs with an average precision of 0.405, a recall of 0.899, and an F1 score of 0.465. We show that side effect knowledge from JCO articles is largely complementary to that from the US Food and Drug Administration (FDA) drug labels. Through integrative correlation analysis, we show that targeted drug-associated side effects positively correlate with their gene targets and disease indications. In conclusion, this unique database that we built from a large number of high-profile oncological articles could facilitate the development of computational models to understand toxic effects associated with targeted anticancer drugs. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Dynamic programming re-ranking for PPI interactor and pair extraction in full-text articles

    Science.gov (United States)

    2011-01-01

    Background Experimentally verified protein-protein interactions (PPIs) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be facilitated by employing text-mining systems to identify genes which play the interactor role in PPIs and to map these genes to unique database identifiers (interactor normalization task or INT) and then to return a list of interaction pairs for each article (interaction pair task or IPT). These two tasks are evaluated in terms of the area under curve of the interpolated precision/recall (AUC iP/R) score because the order of identifiers in the output list is important for ease of curation. Results Our INT system developed for the BioCreAtIvE II.5 INT challenge achieved a promising AUC iP/R of 43.5% by using a support vector machine (SVM)-based ranking procedure. Using our new re-ranking algorithm, we have been able to improve system performance (AUC iP/R) by 1.84%. Our experimental results also show that with the re-ranked INT results, our unsupervised IPT system can achieve a competitive AUC iP/R of 23.86%, which outperforms the best BC II.5 INT system by 1.64%. Compared to using only SVM ranked INT results, using re-ranked INT results boosts AUC iP/R by 7.84%. Statistical significance t-test results show that our INT/IPT system with re-ranking outperforms that without re-ranking by a statistically significant difference. Conclusions In this paper, we present a new re-ranking algorithm that considers co-occurrence among identifiers in an article to improve INT and IPT ranking results. Combining the re-ranked INT results with an unsupervised approach to find associations among interactors, the proposed method can boost the IPT performance. We also implement score computation using dynamic programming, which is faster and more efficient than traditional approaches. PMID:21342534

  6. Extracting 3d Semantic Information from Video Surveillance System Using Deep Learning

    Science.gov (United States)

    Zhang, J. S.; Cao, J.; Mao, B.; Shen, D. Q.

    2018-04-01

    At present, intelligent video analysis technology has been widely used in various fields. Object tracking is one of the important part of intelligent video surveillance, but the traditional target tracking technology based on the pixel coordinate system in images still exists some unavoidable problems. Target tracking based on pixel can't reflect the real position information of targets, and it is difficult to track objects across scenes. Based on the analysis of Zhengyou Zhang's camera calibration method, this paper presents a method of target tracking based on the target's space coordinate system after converting the 2-D coordinate of the target into 3-D coordinate. It can be seen from the experimental results: Our method can restore the real position change information of targets well, and can also accurately get the trajectory of the target in space.

  7. Text-in-context: a method for extracting findings in mixed-methods mixed research synthesis studies.

    Science.gov (United States)

    Sandelowski, Margarete; Leeman, Jennifer; Knafl, Kathleen; Crandell, Jamie L

    2013-06-01

    Our purpose in this paper is to propose a new method for extracting findings from research reports included in mixed-methods mixed research synthesis studies. International initiatives in the domains of systematic review and evidence synthesis have been focused on broadening the conceptualization of evidence, increased methodological inclusiveness and the production of evidence syntheses that will be accessible to and usable by a wider range of consumers. Initiatives in the general mixed-methods research field have been focused on developing truly integrative approaches to data analysis and interpretation. The data extraction challenges described here were encountered, and the method proposed for addressing these challenges was developed, in the first year of the ongoing (2011-2016) study: Mixed-Methods Synthesis of Research on Childhood Chronic Conditions and Family. To preserve the text-in-context of findings in research reports, we describe a method whereby findings are transformed into portable statements that anchor results to relevant information about sample, source of information, time, comparative reference point, magnitude and significance and study-specific conceptions of phenomena. The data extraction method featured here was developed specifically to accommodate mixed-methods mixed research synthesis studies conducted in nursing and other health sciences, but reviewers might find it useful in other kinds of research synthesis studies. This data extraction method itself constitutes a type of integration to preserve the methodological context of findings when statements are read individually and in comparison to each other. © 2012 Blackwell Publishing Ltd.

  8. Extracting recurrent scenarios from narrative texts using a Bayesian network: application to serious occupational accidents with movement disturbance.

    Science.gov (United States)

    Abdat, F; Leclercq, S; Cuny, X; Tissot, C

    2014-09-01

    A probabilistic approach has been developed to extract recurrent serious Occupational Accident with Movement Disturbance (OAMD) scenarios from narrative texts within a prevention framework. Relevant data extracted from 143 accounts was initially coded as logical combinations of generic accident factors. A Bayesian Network (BN)-based model was then built for OAMDs using these data and expert knowledge. A data clustering process was subsequently performed to group the OAMDs into similar classes from generic factor occurrence and pattern standpoints. Finally, the Most Probable Explanation (MPE) was evaluated and identified as the associated recurrent scenario for each class. Using this approach, 8 scenarios were extracted to describe 143 OAMDs in the construction and metallurgy sectors. Their recurrent nature is discussed. Probable generic factor combinations provide a fair representation of particularly serious OAMDs, as described in narrative texts. This work represents a real contribution to raising company awareness of the variety of circumstances, in which these accidents occur, to progressing in the prevention of such accidents and to developing an analysis framework dedicated to this kind of accident. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research.

    Science.gov (United States)

    Bravo, Àlex; Piñero, Janet; Queralt-Rosinach, Núria; Rautschka, Michael; Furlong, Laura I

    2015-02-21

    Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases. By exploiting morpho-syntactic information of the text, BeFree is able to identify gene-disease, drug-disease and drug-target associations with state-of-the-art performance. The application of BeFree to real-case scenarios shows its effectiveness in extracting information relevant for translational research. We show the value of the gene-disease associations extracted by BeFree through a number of analyses and integration with other data sources. BeFree succeeds in identifying genes associated to a major cause of morbidity worldwide, depression, which are not present in other public resources. Moreover, large-scale extraction and analysis of gene-disease associations, and integration with current biomedical knowledge, provided interesting insights on the kind of information that can be found in the literature, and raised challenges regarding data prioritization and curation. We found that only a small proportion of the gene-disease associations discovered by using BeFree is collected in expert-curated databases. Thus, there is a pressing need to find alternative strategies to manual curation, in order to review, prioritize and curate text-mining data and incorporate it into domain-specific databases. We present our strategy for data prioritization and discuss its implications for supporting biomedical research and applications. BeFree is a novel text mining system that performs competitively for the identification of gene-disease, drug-disease and drug-target associations. Our analyses show that mining only a

  10. Extracting a Good Quality Frontal Face Image from a Low-Resolution Video Sequence

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2011-01-01

    Feeding low-resolution and low-quality images, from inexpensive surveillance cameras, to systems like, e.g., face recognition, produces erroneous and unstable results. Therefore, there is a need for a mechanism to bridge the gap between on one hand low-resolution and low-quality images......, we use a learning-based super-resolution algorithm applied to the result of the reconstruction-based part to improve the quality by another factor of two. This results in an improvement factor of four for the entire system. The proposed system has been tested on 122 low-resolution sequences from two...... different databases. The experimental results show that the proposed system can indeed produce a high-resolution and good quality frontal face image from low-resolution video sequences....

  11. Application of Text Analytics to Extract and Analyze Material–Application Pairs from a Large Scientific Corpus

    Directory of Open Access Journals (Sweden)

    Nikhil Kalathil

    2018-01-01

    Full Text Available When assessing the importance of materials (or other components to a given set of applications, machine analysis of a very large corpus of scientific abstracts can provide an analyst a base of insights to develop further. The use of text analytics reduces the time required to conduct an evaluation, while allowing analysts to experiment with a multitude of different hypotheses. Because the scope and quantity of metadata analyzed can, and should, be large, any divergence from what a human analyst determines and what the text analysis shows provides a prompt for the human analyst to reassess any preliminary findings. In this work, we have successfully extracted material–application pairs and ranked them on their importance. This method provides a novel way to map scientific advances in a particular material to the application for which it is used. Approximately 438,000 titles and abstracts of scientific papers published from 1992 to 2011 were used to examine 16 materials. This analysis used coclustering text analysis to associate individual materials with specific clean energy applications, evaluate the importance of materials to specific applications, and assess their importance to clean energy overall. Our analysis reproduced the judgments of experts in assigning material importance to applications. The validated methods were then used to map the replacement of one material with another material in a specific application (batteries.

  12. Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

    Directory of Open Access Journals (Sweden)

    André SANTOS

    2012-07-01

    Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

  13. Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

    Directory of Open Access Journals (Sweden)

    Anália LOURENÇO

    2013-07-01

    Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

  14. Indexed Captioned Searchable Videos: A Learning Companion for STEM Coursework

    Science.gov (United States)

    Tuna, Tayfun; Subhlok, Jaspal; Barker, Lecia; Shah, Shishir; Johnson, Olin; Hovey, Christopher

    2017-02-01

    Videos of classroom lectures have proven to be a popular and versatile learning resource. A key shortcoming of the lecture video format is accessing the content of interest hidden in a video. This work meets this challenge with an advanced video framework featuring topical indexing, search, and captioning (ICS videos). Standard optical character recognition (OCR) technology was enhanced with image transformations for extraction of text from video frames to support indexing and search. The images and text on video frames is analyzed to divide lecture videos into topical segments. The ICS video player integrates indexing, search, and captioning in video playback providing instant access to the content of interest. This video framework has been used by more than 70 courses in a variety of STEM disciplines and assessed by more than 4000 students. Results presented from the surveys demonstrate the value of the videos as a learning resource and the role played by videos in a students learning process. Survey results also establish the value of indexing and search features in a video platform for education. This paper reports on the development and evaluation of ICS videos framework and over 5 years of usage experience in several STEM courses.

  15. Content-based TV sports video retrieval using multimodal analysis

    Science.gov (United States)

    Yu, Yiqing; Liu, Huayong; Wang, Hongbin; Zhou, Dongru

    2003-09-01

    In this paper, we propose content-based video retrieval, which is a kind of retrieval by its semantical contents. Because video data is composed of multimodal information streams such as video, auditory and textual streams, we describe a strategy of using multimodal analysis for automatic parsing sports video. The paper first defines the basic structure of sports video database system, and then introduces a new approach that integrates visual stream analysis, speech recognition, speech signal processing and text extraction to realize video retrieval. The experimental results for TV sports video of football games indicate that the multimodal analysis is effective for video retrieval by quickly browsing tree-like video clips or inputting keywords within predefined domain.

  16. Temporal Segmentation of MPEG Video Streams

    Directory of Open Access Journals (Sweden)

    Janko Calic

    2002-06-01

    Full Text Available Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.

  17. Systematically extracting metal- and solvent-related occupational information from free-text responses to lifetime occupational history questionnaires.

    Science.gov (United States)

    Friesen, Melissa C; Locke, Sarah J; Tornow, Carina; Chen, Yu-Cheng; Koh, Dong-Hee; Stewart, Patricia A; Purdue, Mark; Colt, Joanne S

    2014-06-01

    Lifetime occupational history (OH) questionnaires often use open-ended questions to capture detailed information about study participants' jobs. Exposure assessors use this information, along with responses to job- and industry-specific questionnaires, to assign exposure estimates on a job-by-job basis. An alternative approach is to use information from the OH responses and the job- and industry-specific questionnaires to develop programmable decision rules for assigning exposures. As a first step in this process, we developed a systematic approach to extract the free-text OH responses and convert them into standardized variables that represented exposure scenarios. Our study population comprised 2408 subjects, reporting 11991 jobs, from a case-control study of renal cell carcinoma. Each subject completed a lifetime OH questionnaire that included verbatim responses, for each job, to open-ended questions including job title, main tasks and activities (task), tools and equipment used (tools), and chemicals and materials handled (chemicals). Based on a review of the literature, we identified exposure scenarios (occupations, industries, tasks/tools/chemicals) expected to involve possible exposure to chlorinated solvents, trichloroethylene (TCE) in particular, lead, and cadmium. We then used a SAS macro to review the information reported by study participants to identify jobs associated with each exposure scenario; this was done using previously coded standardized occupation and industry classification codes, and a priori lists of associated key words and phrases related to possibly exposed tasks, tools, and chemicals. Exposure variables representing the occupation, industry, and task/tool/chemicals exposure scenarios were added to the work history records of the study respondents. Our identification of possibly TCE-exposed scenarios in the OH responses was compared to an expert's independently assigned probability ratings to evaluate whether we missed identifying

  18. stil113_0401r -- Point coverage of locations of still frames extracted from video imagery which depict sediment types

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  19. Coding Local and Global Binary Visual Features Extracted From Video Sequences

    Science.gov (United States)

    Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

    2015-11-01

    Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks, while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the Bag-of-Visual-Word (BoVW) model. Several applications, including for example visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget, while attaining a target level of efficiency. In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can be conveniently adopted to support the Analyze-Then-Compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the Compress-Then-Analyze (CTA) paradigm. In this paper we experimentally compare ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.

  20. Coding Local and Global Binary Visual Features Extracted From Video Sequences.

    Science.gov (United States)

    Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

    2015-11-01

    Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

  1. EXTRACT

    DEFF Research Database (Denmark)

    Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra

    2016-01-01

    The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have the...... and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/......., organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual...

  2. [Treatment-refractory-dental-extraction-associated pyothorax involving infection by 2 species of oral originated bacteria requires surgical debridement by video assisted thoracoscopic surgery (VATS)].

    Science.gov (United States)

    Rai, Kammei; Matsuo, Kiyoshi; Yonei, Toshiro; Sato, Toshio

    2008-09-01

    Cases of septic pulmonary embolism (SPE) diagnosed clinically by CT after dental extraction rarely include verification of bacteria from the local infection site. We report the case of a 70-year-old man without background disease suffering severe pyothrax after dental extraction. We detected two species of oral bacteria from his pleural effusion. Treatment was so difficult that it required surgical debridement by video assisted thoracoscopic surgery (VATS), even after the appropriate administration of antibiotics. According to the American Heart Association (AHA) prophylaxis guidelines for preventing infective endocarditis indicate that it is uncommon to prescribe antibiotics to patients without background disease after dental extraction. No appropriate Japanese guidelines exist considering the prevention of SPE causing severe pyothorax as in our case. The hematogenous spread of bacteria such as SPE caused by sepsis after tooth extraction thus requires more attended careful consideration in clinical practice if patients are to be properly protected against potentially serious complications.

  3. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-01-01

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images. PMID:28335510

  4. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction.

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-03-20

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  5. Multimedia Information Extraction

    CERN Document Server

    Maybury, Mark T

    2012-01-01

    The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance.  While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and vid

  6. Combining position weight matrices and document-term matrix for efficient extraction of associations of methylated genes and diseases from free text.

    Directory of Open Access Journals (Sweden)

    Arwa Bin Raies

    Full Text Available BACKGROUND: In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually. METHODOLOGY: We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text. CONCLUSION: The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download.

  7. Combining Position Weight Matrices and Document-Term Matrix for Efficient Extraction of Associations of Methylated Genes and Diseases from Free Text

    KAUST Repository

    Bin Raies, Arwa

    2013-10-16

    Background:In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually.Methodology:We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs) for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text.Conclusion:The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download. © 2013 Bin Raies et al.

  8. stil119_0601a -- Point coverage of locations of still frames extracted from video imagery which depict sediment types

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Canadian ROPOS remotely operated vehicle (ROV) outfitted with video equipment (and other devices) was deployed from the NOAA Ship McAurthurII during May-June...

  9. Automated Trait Extraction using ClearEarth, a Natural Language Processing System for Text Mining in Natural Sciences

    OpenAIRE

    Thessen,Anne; Preciado,Jenette; Jain,Payoj; Martin,James; Palmer,Martha; Bhat,Riyaz

    2018-01-01

    The cTAKES package (using the ClearTK Natural Language Processing toolkit Bethard et al. 2014, http://cleartk.github.io/cleartk/) has been successfully used to automatically read clinical notes in the medical field (Albright et al. 2013, Styler et al. 2014). It is used on a daily basis to automatically process clinical notes and extract relevant information by dozens of medical institutions. ClearEarth is a collaborative project that brings together computational linguistics and domain scient...

  10. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... member of our patient care team. Managing Your Arthritis Managing Your Arthritis Managing Chronic Pain and Depression ...

  11. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia ... *PDF files require the free Adobe® Reader® software for viewing. This website is maintained by the ...

  12. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... questions Clinical Studies Publications Catalog Photos and Images Spanish Language Information Grants and Funding Extramural Research Division ... Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video ...

  13. Fast Aerial Video Stitching

    Directory of Open Access Journals (Sweden)

    Jing Li

    2014-10-01

    Full Text Available The highly efficient and robust stitching of aerial video captured by unmanned aerial vehicles (UAVs is a challenging problem in the field of robot vision. Existing commercial image stitching systems have seen success with offline stitching tasks, but they cannot guarantee high-speed performance when dealing with online aerial video sequences. In this paper, we present a novel system which has an unique ability to stitch high-frame rate aerial video at a speed of 150 frames per second (FPS. In addition, rather than using a high-speed vision platform such as FPGA or CUDA, our system is running on a normal personal computer. To achieve this, after the careful comparison of the existing invariant features, we choose the FAST corner and binary descriptor for efficient feature extraction and representation, and present a spatial and temporal coherent filter to fuse the UAV motion information into the feature matching. The proposed filter can remove the majority of feature correspondence outliers and significantly increase the speed of robust feature matching by up to 20 times. To achieve a balance between robustness and efficiency, a dynamic key frame-based stitching framework is used to reduce the accumulation errors. Extensive experiments on challenging UAV datasets demonstrate that our approach can break through the speed limitation and generate an accurate stitching image for aerial video stitching tasks.

  14. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork Peer ... me? Find a group Back Upcoming events Video Library Photo Gallery One-on-One Support Back ANetwork ...

  15. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Doctor Find a Provider Meet the Team Blog Articles & Stories News Resources Links Videos Podcasts Webinars For ... Doctor Find a Provider Meet the Team Blog Articles & Stories News Provider Directory Donate Resources Links Videos ...

  16. An Enhanced Text-Mining Framework for Extracting Disaster Relevant Data through Social Media and Remote Sensing Data Fusion

    Science.gov (United States)

    Scheele, C. J.; Huang, Q.

    2016-12-01

    In the past decade, the rise in social media has led to the development of a vast number of social media services and applications. Disaster management represents one of such applications leveraging massive data generated for event detection, response, and recovery. In order to find disaster relevant social media data, current approaches utilize natural language processing (NLP) methods based on keywords, or machine learning algorithms relying on text only. However, these approaches cannot be perfectly accurate due to the variability and uncertainty in language used on social media. To improve current methods, the enhanced text-mining framework is proposed to incorporate location information from social media and authoritative remote sensing datasets for detecting disaster relevant social media posts, which are determined by assessing the textual content using common text mining methods and how the post relates spatiotemporally to the disaster event. To assess the framework, geo-tagged Tweets were collected for three different spatial and temporal disaster events: hurricane, flood, and tornado. Remote sensing data and products for each event were then collected using RealEarthTM. Both Naive Bayes and Logistic Regression classifiers were used to compare the accuracy within the enhanced text-mining framework. Finally, the accuracies from the enhanced text-mining framework were compared to the current text-only methods for each of the case study disaster events. The results from this study address the need for more authoritative data when using social media in disaster management applications.

  17. Design and Implementation of Video Shot Detection on Field Programmable Gate Arrays

    Directory of Open Access Journals (Sweden)

    Jharna Majumdar

    2012-09-01

    Full Text Available Video has become an interactive medium of communication in everyday life. The sheer volume of video makes it extremely difficult to browse through and find the required data. Hence extraction of key frames from the video which represents the abstract of the entire video becomes necessary. The aim of the video shot detection is to find the position of the shot boundaries, so that key frames can be selected from each shot for subsequent processing such as video summarization, indexing etc. For most of the surveillance applications like video summery, face recognition etc., the hardware (real time implementation of these algorithms becomes necessary. Here in this paper we present the architecture for simultaneous accessing of consecutive frames, which are then used for the implementation of various Video Shot Detection algorithms. We also present the real time implementation of three video shot detection algorithms using the above mentioned architecture on FPGA (Field Programmable Gate Arrays.

  18. MPEG-2 Compressed-Domain Algorithms for Video Analysis

    Directory of Open Access Journals (Sweden)

    Hesseler Wolfgang

    2006-01-01

    Full Text Available This paper presents new algorithms for extracting metadata from video sequences in the MPEG-2 compressed domain. Three algorithms for efficient low-level metadata extraction in preprocessing stages are described. The first algorithm detects camera motion using the motion vector field of an MPEG-2 video. The second method extends the idea of motion detection to a limited region of interest, yielding an efficient algorithm to track objects inside video sequences. The third algorithm performs a cut detection using macroblock types and motion vectors.

  19. Extraction of Pluvial Flood Relevant Volunteered Geographic Information (VGI by Deep Learning from User Generated Texts and Photos

    Directory of Open Access Journals (Sweden)

    Yu Feng

    2018-01-01

    Full Text Available In recent years, pluvial floods caused by extreme rainfall events have occurred frequently. Especially in urban areas, they lead to serious damages and endanger the citizens’ safety. Therefore, real-time information about such events is desirable. With the increasing popularity of social media platforms, such as Twitter or Instagram, information provided by voluntary users becomes a valuable source for emergency response. Many applications have been built for disaster detection and flood mapping using crowdsourcing. Most of the applications so far have merely used keyword filtering or classical language processing methods to identify disaster relevant documents based on user generated texts. As the reliability of social media information is often under criticism, the precision of information retrieval plays a significant role for further analyses. Thus, in this paper, high quality eyewitnesses of rainfall and flooding events are retrieved from social media by applying deep learning approaches on user generated texts and photos. Subsequently, events are detected through spatiotemporal clustering and visualized together with these high quality eyewitnesses in a web map application. Analyses and case studies are conducted during flooding events in Paris, London and Berlin.

  20. Application of Text Mining to Extract Hotel Attributes and Construct Perceptual Map of Five Star Hotels from Online Review: Study of Jakarta and Singapore Five-Star Hotels

    Directory of Open Access Journals (Sweden)

    Arga Hananto

    2015-12-01

    Full Text Available The use of post-purchase online consumer review in hotel attributes study was still scarce in the literature. Arguably, post purchase online review data would gain more accurate attributes thatconsumers actually consider in their purchase decision. This study aims to extract attributes from two samples of five-star hotel reviews (Jakarta and Singapore with text mining methodology. In addition,this study also aims to describe positioning of five-star hotels in Jakarta and Singapore based on the extracted attributes using Correspondence Analysis. This study finds that reviewers of five star hotels in both cities mentioned similar attributes such as service, staff, club, location, pool and food. Attributes derived from text mining seem to be viable input to build fairly accurate positioning map of hotels. This study has demonstrated the viability of online review as a source of data for hotel attribute and positioning studies.

  1. ADEPt, a semantically-enriched pipeline for extracting adverse drug events from free-text electronic health records.

    Directory of Open Access Journals (Sweden)

    Ehtesham Iqbal

    Full Text Available Adverse drug events (ADEs are unintended responses to medical treatment. They can greatly affect a patient's quality of life and present a substantial burden on healthcare. Although Electronic health records (EHRs document a wealth of information relating to ADEs, they are frequently stored in the unstructured or semi-structured free-text narrative requiring Natural Language Processing (NLP techniques to mine the relevant information. Here we present a rule-based ADE detection and classification pipeline built and tested on a large Psychiatric corpus comprising 264k patients using the de-identified EHRs of four UK-based psychiatric hospitals. The pipeline uses characteristics specific to Psychiatric EHRs to guide the annotation process, and distinguishes: a the temporal value associated with the ADE mention (whether it is historical or present, b the categorical value of the ADE (whether it is assertive, hypothetical, retrospective or a general discussion and c the implicit contextual value where the status of the ADE is deduced from surrounding indicators, rather than explicitly stated. We manually created the rulebase in collaboration with clinicians and pharmacists by studying ADE mentions in various types of clinical notes. We evaluated the open-source Adverse Drug Event annotation Pipeline (ADEPt using 19 ADEs specific to antipsychotics and antidepressants medication. The ADEs chosen vary in severity, regularity and persistence. The average F-measure and accuracy achieved by our tool across all tested ADEs were 0.83 and 0.83 respectively. In addition to annotation power, the ADEPT pipeline presents an improvement to the state of the art context-discerning algorithm, ConText.

  2. The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records

    Directory of Open Access Journals (Sweden)

    Shah Anoop D

    2012-08-01

    Full Text Available Abstract Background Electronic health records are invaluable for medical research, but much information is stored as free text rather than in a coded form. For example, in the UK General Practice Research Database (GPRD, causes of death and test results are sometimes recorded only in free text. Free text can be difficult to use for research if it requires time-consuming manual review. Our aim was to develop an automated method for extracting coded information from free text in electronic patient records. Methods We reviewed the electronic patient records in GPRD of a random sample of 3310 patients who died in 2001, to identify the cause of death. We developed a computer program called the Freetext Matching Algorithm (FMA to map diagnoses in text to the Read Clinical Terminology. The program uses lookup tables of synonyms and phrase patterns to identify diagnoses, dates and selected test results. We tested it on two random samples of free text from GPRD (1000 texts associated with death in 2001, and 1000 general texts from cases and controls in a coronary artery disease study, comparing the output to the U.S. National Library of Medicine’s MetaMap program and the gold standard of manual review. Results Among 3310 patients registered in the GPRD who died in 2001, the cause of death was recorded in coded form in 38.1% of patients, and in the free text alone in 19.4%. On the 1000 texts associated with death, FMA coded 683 of the 735 positive diagnoses, with precision (positive predictive value 98.4% (95% confidence interval (CI 97.2, 99.2 and recall (sensitivity 92.9% (95% CI 90.8, 94.7. On the general sample, FMA detected 346 of the 447 positive diagnoses, with precision 91.5% (95% CI 88.3, 94.1 and recall 77.4% (95% CI 73.2, 81.2, which was similar to MetaMap. Conclusions We have developed an algorithm to extract coded information from free text in GP records with good precision. It may facilitate research using free text in electronic patient

  3. ZK DrugResist 2.0: A TextMiner to extract semantic relations of drug resistance from PubMed.

    Science.gov (United States)

    Khalid, Zoya; Sezerman, Osman Ugur

    2017-05-01

    Extracting useful knowledge from an unstructured textual data is a challenging task for biologists, since biomedical literature is growing exponentially on a daily basis. Building an automated method for such tasks is gaining much attention of researchers. ZK DrugResist is an online tool that automatically extracts mutations and expression changes associated with drug resistance from PubMed. In this study we have extended our tool to include semantic relations extracted from biomedical text covering drug resistance and established a server including both of these features. Our system was tested for three relations, Resistance (R), Intermediate (I) and Susceptible (S) by applying hybrid feature set. From the last few decades the focus has changed to hybrid approaches as it provides better results. In our case this approach combines rule-based methods with machine learning techniques. The results showed 97.67% accuracy with 96% precision, recall and F-measure. The results have outperformed the previously existing relation extraction systems thus can facilitate computational analysis of drug resistance against complex diseases and further can be implemented on other areas of biomedicine. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. NEI You Tube Videos: Amblyopia

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    Full Text Available ... search for current job openings visit HHS USAJobs Home >> NEI YouTube Videos >> NEI YouTube Videos: Amblyopia Listen NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract ...

  5. NEI You Tube Videos: Amblyopia

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    Full Text Available ... Amaurosis Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia NEI Home Contact Us A-Z Site Map NEI on Social Media Information in Spanish (Información en español) Website, ...

  6. NEI You Tube Videos: Amblyopia

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    Full Text Available ... search for current job openings visit HHS USAJobs Home » NEI YouTube Videos » NEI YouTube Videos: Amblyopia Listen NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract ...

  7. Anthropocentric Video Segmentation for Lecture Webcasts

    Directory of Open Access Journals (Sweden)

    Rojas Raul

    2007-01-01

    Full Text Available Abstract Many lecture recording and presentation systems transmit slides or chalkboard content along with a small video of the instructor. As a result, two areas of the screen are competing for the viewer's attention, causing the widely known split-attention effect. Face and body gestures, such as pointing, do not appear in the context of the slides or the board. To eliminate this problem, this article proposes to extract the lecturer from the video stream and paste his or her image onto the board or slide image. As a result, the lecturer acting in front of the board or slides becomes the center of attention. The entire lecture presentation becomes more human-centered. This article presents both an analysis of the underlying psychological problems and an explanation of signal processing techniques that are applied in a concrete system. The presented algorithm is able to extract and overlay the lecturer online and in real time at full video resolution.

  8. Anthropocentric Video Segmentation for Lecture Webcasts

    Directory of Open Access Journals (Sweden)

    Raul Rojas

    2008-03-01

    Full Text Available Many lecture recording and presentation systems transmit slides or chalkboard content along with a small video of the instructor. As a result, two areas of the screen are competing for the viewer's attention, causing the widely known split-attention effect. Face and body gestures, such as pointing, do not appear in the context of the slides or the board. To eliminate this problem, this article proposes to extract the lecturer from the video stream and paste his or her image onto the board or slide image. As a result, the lecturer acting in front of the board or slides becomes the center of attention. The entire lecture presentation becomes more human-centered. This article presents both an analysis of the underlying psychological problems and an explanation of signal processing techniques that are applied in a concrete system. The presented algorithm is able to extract and overlay the lecturer online and in real time at full video resolution.

  9. Advanced video coding systems

    CERN Document Server

    Gao, Wen

    2015-01-01

    This comprehensive and accessible text/reference presents an overview of the state of the art in video coding technology. Specifically, the book introduces the tools of the AVS2 standard, describing how AVS2 can help to achieve a significant improvement in coding efficiency for future video networks and applications by incorporating smarter coding tools such as scene video coding. Topics and features: introduces the basic concepts in video coding, and presents a short history of video coding technology and standards; reviews the coding framework, main coding tools, and syntax structure of AV

  10. Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER)system.

    Science.gov (United States)

    Pandey, Abhishek; Kreimeyer, Kory; Foster, Matthew; Botsis, Taxiarchis; Dang, Oanh; Ly, Thomas; Wang, Wei; Forshee, Richard

    2018-01-01

    Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

  11. Combining Recurrence Analysis and Automatic Movement Extraction from Video Recordings to Study Behavioral Coupling in Face-to-Face Parent-Child Interactions.

    Science.gov (United States)

    López Pérez, David; Leonardi, Giuseppe; Niedźwiecka, Alicja; Radkowska, Alicja; Rączaszek-Leonardi, Joanna; Tomalski, Przemysław

    2017-01-01

    The analysis of parent-child interactions is crucial for the understanding of early human development. Manual coding of interactions is a time-consuming task, which is a limitation in many projects. This becomes especially demanding if a frame-by-frame categorization of movement needs to be achieved. To overcome this, we present a computational approach for studying movement coupling in natural settings, which is a combination of a state-of-the-art automatic tracker, Tracking-Learning-Detection (TLD), and nonlinear time-series analysis, Cross-Recurrence Quantification Analysis (CRQA). We investigated the use of TLD to extract and automatically classify movement of each partner from 21 video recordings of interactions, where 5.5-month-old infants and mothers engaged in free play in laboratory settings. As a proof of concept, we focused on those face-to-face episodes, where the mother animated an object in front of the infant, in order to measure the coordination between the infants' head movement and the mothers' hand movement. We also tested the feasibility of using such movement data to study behavioral coupling between partners with CRQA. We demonstrate that movement can be extracted automatically from standard definition video recordings and used in subsequent CRQA to quantify the coupling between movement of the parent and the infant. Finally, we assess the quality of this coupling using an extension of CRQA called anisotropic CRQA and show asymmetric dynamics between the movement of the parent and the infant. When combined these methods allow automatic coding and classification of behaviors, which results in a more efficient manner of analyzing movements than manual coding.

  12. SECRETS OF SONG VIDEO

    Directory of Open Access Journals (Sweden)

    Chernyshov Alexander V.

    2014-04-01

    Full Text Available The article focuses on the origins of the song videos as TV and Internet-genre. In addition, it considers problems of screen images creation depending on the musical form and the text of a songs in connection with relevant principles of accent and phraseological video editing and filming techniques as well as with additional frames and sound elements.

  13. Sequence to Sequence - Video to Text

    Science.gov (United States)

    2015-12-11

    by centering x and y flow values around 128 and multiplying by a scalar such that flow values fall between 0 and 255. We also calculate the flow magni...as for MPII- MD. 4.2. Evaluation Metrics Quantitative evaluation of the models are performed us- ing the METEOR [7] metric which was originally pro...candidate refer- ence sentences. METEOR compares exact token matches, stemmed tokens, paraphrase matches, as well as semanti- cally similar matches

  14. A Standard-Compliant Virtual Meeting System with Active Video Object Tracking

    Directory of Open Access Journals (Sweden)

    Chang Yao-Jen

    2002-01-01

    Full Text Available This paper presents an H.323 standard compliant virtual video conferencing system. The proposed system not only serves as a multipoint control unit (MCU for multipoint connection but also provides a gateway function between the H.323 LAN (local-area network and the H.324 WAN (wide-area network users. The proposed virtual video conferencing system provides user-friendly object compositing and manipulation features including 2D video object scaling, repositioning, rotation, and dynamic bit-allocation in a 3D virtual environment. A reliable, and accurate scheme based on background image mosaics is proposed for real-time extracting and tracking foreground video objects from the video captured with an active camera. Chroma-key insertion is used to facilitate video objects extraction and manipulation. We have implemented a prototype of the virtual conference system with an integrated graphical user interface to demonstrate the feasibility of the proposed methods.

  15. Segmentation Based Video Steganalysis to Detect Motion Vector Modification

    Directory of Open Access Journals (Sweden)

    Peipei Wang

    2017-01-01

    Full Text Available This paper presents a steganalytic approach against video steganography which modifies motion vector (MV in content adaptive manner. Current video steganalytic schemes extract features from fixed-length frames of the whole video and do not take advantage of the content diversity. Consequently, the effectiveness of the steganalytic feature is influenced by video content and the problem of cover source mismatch also affects the steganalytic performance. The goal of this paper is to propose a steganalytic method which can suppress the differences of statistical characteristics caused by video content. The given video is segmented to subsequences according to block’s motion in every frame. The steganalytic features extracted from each category of subsequences with close motion intensity are used to build one classifier. The final steganalytic result can be obtained by fusing the results of weighted classifiers. The experimental results have demonstrated that our method can effectively improve the performance of video steganalysis, especially for videos of low bitrate and low embedding ratio.

  16. Reflections on academic video

    Directory of Open Access Journals (Sweden)

    Thommy Eriksson

    2012-11-01

    Full Text Available As academics we study, research and teach audiovisual media, yet rarely disseminate and mediate through it. Today, developments in production technologies have enabled academic researchers to create videos and mediate audiovisually. In academia it is taken for granted that everyone can write a text. Is it now time to assume that everyone can make a video essay? Using the online journal of academic videos Audiovisual Thinking and the videos published in it as a case study, this article seeks to reflect on the emergence and legacy of academic audiovisual dissemination. Anchoring academic video and audiovisual dissemination of knowledge in two critical traditions, documentary theory and semiotics, we will argue that academic video is in fact already present in a variety of academic disciplines, and that academic audiovisual essays are bringing trends and developments that have long been part of academic discourse to their logical conclusion.

  17. still116_0501d-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  18. Olympic Coast National Marine Sanctuary - stil120_0602a - Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during September 2006. Video data...

  19. still115_0403-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  20. still114_0402c-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  1. still114_0402b-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  2. still116_0501c-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  3. still116_0501s-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  4. still116_0501n-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vesselTatoosh during August 2005. Video data from...

  5. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Videos for Educators Search English Español Special Needs: Planning for Adulthood (Video) KidsHealth / For Parents / Special Needs: Planning for Adulthood (Video) Print Young adults with special ...

  6. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... Staying Safe Videos for Educators Search English Español Special Needs: Planning for Adulthood (Video) KidsHealth / For Parents / Special Needs: Planning for Adulthood (Video) Print Young adults with ...

  7. A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

    Directory of Open Access Journals (Sweden)

    Shengcheng Ma

    2018-01-01

    Full Text Available This paper investigates and analyzes the characteristics of video data and puts forward a campus surveillance video storage system with the university campus as the specific application environment. Aiming at the challenge that the content-based video retrieval response time is too long, the key-frame index subsystem is designed. The key frame of the video can reflect the main content of the video. Extracted from the video, key frames are associated with the metadata information to establish the storage index. The key-frame index is used in lookup operations while querying. This method can greatly reduce the amount of video data reading and effectively improves the query’s efficiency. From the above, we model the storage system by a stochastic Petri net (SPN and verify the promotion of query performance by quantitative analysis.

  8. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... will allow you to take a more active role in your care. The information in these videos ... Stategies to Increase your Level of Physical Activity Role of Body Weight in Osteoarthritis Educational Videos for ...

  9. NEI You Tube Videos: Amblyopia

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    Full Text Available ... Eye Disease Dilated Eye Exam Dry Eye For Kids Glaucoma Healthy Vision Tips Leber Congenital Amaurosis Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded ...

  10. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... of Body Weight in Osteoarthritis Educational Videos for Patients Rheumatoid Arthritis Educational Video Series Psoriatic Arthritis 101 ... Patient to an Adult Rheumatologist Drug Information for Patients Arthritis Drug Information Sheets Benefits and Risks of ...

  11. Dashboard Videos

    Science.gov (United States)

    Gleue, Alan D.; Depcik, Chris; Peltier, Ted

    2012-01-01

    Last school year, I had a web link emailed to me entitled "A Dashboard Physics Lesson." The link, created and posted by Dale Basier on his "Lab Out Loud" blog, illustrates video of a car's speedometer synchronized with video of the road. These two separate video streams are compiled into one video that students can watch and analyze. After seeing…

  12. Video microblogging

    DEFF Research Database (Denmark)

    Bornoe, Nis; Barkhuus, Louise

    2010-01-01

    Microblogging is a recently popular phenomenon and with the increasing trend for video cameras to be built into mobile phones, a new type of microblogging has entered the arena of electronic communication: video microblogging. In this study we examine video microblogging, which is the broadcasting...... of short videos. A series of semi-structured interviews offers an understanding of why and how video microblogging is used and what the users post and broadcast....

  13. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... videos from Veterans Health Administration Veterans Crisis Line -- After the Call see more videos from Veterans Health ... videos from Veterans Health Administration Talking About It Matters see more videos from Veterans Health Administration Stand ...

  14. Video demystified

    CERN Document Server

    Jack, Keith

    2004-01-01

    This international bestseller and essential reference is the "bible" for digital video engineers and programmers worldwide. This is by far the most informative analog and digital video reference available, includes the hottest new trends and cutting-edge developments in the field. Video Demystified, Fourth Edition is a "one stop" reference guide for the various digital video technologies. The fourth edition is completely updated with all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video (Video over DSL, Ethernet, etc.), as well as discussions of the latest standards throughout. The accompanying CD-ROM is updated to include a unique set of video test files in the newest formats. *This essential reference is the "bible" for digital video engineers and programmers worldwide *Contains all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video *Completely revised with all the latest and most up-to-date industry standards.

  15. Video pedagogy

    OpenAIRE

    Länsitie, Janne; Stevenson, Blair; Männistö, Riku; Karjalainen, Tommi; Karjalainen, Asko

    2016-01-01

    The short film is an introduction to the concept of video pedagogy. The five categories of video pedagogy further elaborate how videos can be used as a part of instruction and learning process. Most pedagogical videos represent more than one category. A video itself doesn’t necessarily define the category – the ways in which the video is used as a part of pedagogical script are more defining factors. What five categories did you find? Did you agree with the categories, or are more...

  16. Camera network video summarization

    Science.gov (United States)

    Panda, Rameswar; Roy-Chowdhury, Amit K.

    2017-05-01

    Networks of vision sensors are deployed in many settings, ranging from security needs to disaster response to environmental monitoring. Many of these setups have hundreds of cameras and tens of thousands of hours of video. The difficulty of analyzing such a massive volume of video data is apparent whenever there is an incident that requires foraging through vast video archives to identify events of interest. As a result, video summarization, that automatically extract a brief yet informative summary of these videos, has attracted intense attention in the recent years. Much progress has been made in developing a variety of ways to summarize a single video in form of a key sequence or video skim. However, generating a summary from a set of videos captured in a multi-camera network still remains as a novel and largely under-addressed problem. In this paper, with the aim of summarizing videos in a camera network, we introduce a novel representative selection approach via joint embedding and capped l21-norm minimization. The objective function is two-fold. The first is to capture the structural relationships of data points in a camera network via an embedding, which helps in characterizing the outliers and also in extracting a diverse set of representatives. The second is to use a capped l21-norm to model the sparsity and to suppress the influence of data outliers in representative selection. We propose to jointly optimize both of the objectives, such that embedding can not only characterize the structure, but also indicate the requirements of sparse representative selection. Extensive experiments on standard multi-camera datasets well demonstrate the efficacy of our method over state-of-the-art methods.

  17. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... Your Arthritis Managing Chronic Pain and Depression in Arthritis Nutrition & Rheumatoid Arthritis Arthritis and Health-related Quality of Life ...

  18. Contemplation, Subcreation, and Video Games

    Directory of Open Access Journals (Sweden)

    Mark J. P. Wolf

    2018-04-01

    Full Text Available This essay asks how religion and theological ideas might be made manifest in video games, and particularly the creation of video games as a religious activity, looking at contemplative experiences in video games, and the creation and world-building of game worlds as a form of Tolkienian subcreation, which itself leads to contemplation regarding the creation of worlds.

  19. Parkinson's Disease Videos

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    Full Text Available ... Nonmotor Symptoms of Parkinson's Disease Expert Briefings: Gait, Balance and Falls in Parkinson's Disease Expert Briefings: Coping ... Library is an extensive collection of books, fact sheets, videos, podcasts, and more. To get started, use ...

  20. Acoustic Neuroma Educational Video

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    Full Text Available ... Facts What is acoustic neuroma? Diagnosing Symptoms Side Effects Keywords World Language Videos Questions to ask Choosing ... Surgery What is acoustic neuroma Diagnosing Symptoms Side effects Question To Ask Treatment Options Back Overview Observation ...

  1. Acoustic Neuroma Educational Video

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    Full Text Available ... 8211 info@ANAUSA.org About ANA Mission, Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video English English Arabic Catalan Chinese (Simplified) Chinese ( ...

  2. Videos, Podcasts and Livechats

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  3. Acoustic Neuroma Educational Video

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  4. Acoustic Neuroma Educational Video

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  5. Acoustic Neuroma Educational Video

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    Full Text Available ... Mission, Vision & Values Shop ANA Leadership & Staff Annual Reports Acoustic Neuroma Association 600 Peachtree Parkway Suite 108 ... About ANA Mission, Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video English English ...

  6. Videos, Podcasts and Livechats

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    Full Text Available ... Search Search What Is It Definition Pediatric Palliative Care Disease Types FAQ Handout for Patients and Families ... For Family Caregivers Glossary Resources Browse our palliative care resources below: Links Videos Podcasts Webinars For the ...

  7. Acoustic Neuroma Educational Video

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    Full Text Available ... About ANA Mission, Vision & Values Shop ANA Leadership & Staff Annual Reports Acoustic Neuroma Association 600 Peachtree Parkway ... ANAUSA.org About ANA Mission, Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video ...

  8. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... info@ANAUSA.org About ANA Mission, Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video English English Arabic Catalan Chinese (Simplified) Chinese ( ...

  9. Videos, Podcasts and Livechats

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    Full Text Available ... to your Doctor Find a Provider Meet the Team Blog Articles & Stories News Resources Links Videos Podcasts ... to your Doctor Find a Provider Meet the Team Blog Articles & Stories News Provider Directory Donate Resources ...

  10. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Click to learn more... LOGIN CALENDAR DONATE NEWS Home Learn Back Learn about acoustic neuroma AN Facts ... Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video English English Arabic Catalan Chinese ( ...

  11. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... the Media For Clinicians For Policymakers For Family Caregivers Glossary Menu In this section Links Videos Podcasts ... the Media For Clinicians For Policymakers For Family Caregivers Glossary Resources Browse our palliative care resources below: ...

  12. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  13. Video Sensor Architecture for Surveillance Applications

    Directory of Open Access Journals (Sweden)

    José E. Simó

    2012-02-01

    Full Text Available This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

  14. GIF Video Sentiment Detection Using Semantic Sequence

    Directory of Open Access Journals (Sweden)

    Dazhen Lin

    2017-01-01

    Full Text Available With the development of social media, an increasing number of people use short videos in social media applications to express their opinions and sentiments. However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. In this context, we propose a SentiPair Sequence based GIF video sentiment detection approach with two contributions. First, we propose a Synset Forest method to extract sentiment related semantic concepts from WordNet to build a robust SentiPair label set. This approach considers the semantic gap between label words and selects a robust label subset which is related to sentiment. Secondly, we propose a SentiPair Sequence based GIF video sentiment detection approach that learns the semantic sequence to understand the sentiment from GIF videos. Our experiment results on GSO-2016 (GIF Sentiment Ontology data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art middle level sentiment ontology features, Adjective Noun Pairs (ANPs.

  15. Obscene Video Recognition Using Fuzzy SVM and New Sets of Features

    Directory of Open Access Journals (Sweden)

    Alireza Behrad

    2013-02-01

    Full Text Available In this paper, a novel approach for identifying normal and obscene videos is proposed. In order to classify different episodes of a video independently and discard the need to process all frames, first, key frames are extracted and skin regions are detected for groups of video frames starting with key frames. In the second step, three different features including 1- structural features based on single frame information, 2- features based on spatiotemporal volume and 3-motion-based features, are extracted for each episode of video. The PCA-LDA method is then applied to reduce the size of structural features and select more distinctive features. For the final step, we use fuzzy or a Weighted Support Vector Machine (WSVM classifier to identify video episodes. We also employ a multilayer Kohonen network as an initial clustering algorithm to increase the ability to discriminate between the extracted features into two classes of videos. Features based on motion and periodicity characteristics increase the efficiency of the proposed algorithm in videos with bad illumination and skin colour variation. The proposed method is evaluated using 1100 videos in different environmental and illumination conditions. The experimental results show a correct recognition rate of 94.2% for the proposed algorithm.

  16. An Aerial Video Stabilization Method Based on SURF Feature

    Directory of Open Access Journals (Sweden)

    Wu Hao

    2016-01-01

    Full Text Available The video captured by Micro Aerial Vehicle is often degraded due to unexpected random trembling and jitter caused by wind and the shake of the aerial platform. An approach for stabilizing the aerial video based on SURF feature and Kalman filter is proposed. SURF feature points are extracted in each frame, and the feature points between adjacent frames are matched using Fast Library for Approximate Nearest Neighbors search method. Then Random Sampling Consensus matching algorithm and Least Squares Method are used to remove mismatching points pairs, and estimate the transformation between the adjacent images. Finally, Kalman filter is applied to smooth the motion parameters and separate Intentional Motion from Unwanted Motion to stabilize the aerial video. Experiments results show that the approach can stabilize aerial video efficiently with high accuracy, and it is robust to the translation, rotation and zooming motion of camera.

  17. Joint Rendering and Segmentation of Free-Viewpoint Video

    Directory of Open Access Journals (Sweden)

    Ishii Masato

    2010-01-01

    Full Text Available Abstract This paper presents a method that jointly performs synthesis and object segmentation of free-viewpoint video using multiview video as the input. This method is designed to achieve robust segmentation from online video input without per-frame user interaction and precomputations. This method shares a calculation process between the synthesis and segmentation steps; the matching costs calculated through the synthesis step are adaptively fused with other cues depending on the reliability in the segmentation step. Since the segmentation is performed for arbitrary viewpoints directly, the extracted object can be superimposed onto another 3D scene with geometric consistency. We can observe that the object and new background move naturally along with the viewpoint change as if they existed together in the same space. In the experiments, our method can process online video input captured by a 25-camera array and show the result image at 4.55 fps.

  18. Immersive video

    Science.gov (United States)

    Moezzi, Saied; Katkere, Arun L.; Jain, Ramesh C.

    1996-03-01

    Interactive video and television viewers should have the power to control their viewing position. To make this a reality, we introduce the concept of Immersive Video, which employs computer vision and computer graphics technologies to provide remote users a sense of complete immersion when viewing an event. Immersive Video uses multiple videos of an event, captured from different perspectives, to generate a full 3D digital video of that event. That is accomplished by assimilating important information from each video stream into a comprehensive, dynamic, 3D model of the environment. Using this 3D digital video, interactive viewers can then move around the remote environment and observe the events taking place from any desired perspective. Our Immersive Video System currently provides interactive viewing and `walkthrus' of staged karate demonstrations, basketball games, dance performances, and typical campus scenes. In its full realization, Immersive Video will be a paradigm shift in visual communication which will revolutionize television and video media, and become an integral part of future telepresence and virtual reality systems.

  19. Text Mining.

    Science.gov (United States)

    Trybula, Walter J.

    1999-01-01

    Reviews the state of research in text mining, focusing on newer developments. The intent is to describe the disparate investigations currently included under the term text mining and provide a cohesive structure for these efforts. A summary of research identifies key organizations responsible for pushing the development of text mining. A section…

  20. stil113_0401p -- Still frame locations of sediment extracted from video imagery collected by Delta submersible in September 2001.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Delta submersible vehicle, outfitted with video equipment (and other devices), was deployed from the R/V Auriga during September 2001 to monitor seafloor...

  1. Olympic Coast National Marine Sanctuary - stil110_0204c - Still frame shots of sediment extracted from video for survey area 110_0204c

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfit with video equipment, lasers and lights was deployed from the NOAA research vessel Tatoosh during the month of September 2006 and...

  2. Olympic Coast National Marine Sanctuary - stil110_0204a - Still frame shots of sediment extracted from video for survey area 110_0204a.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfit with video equipment, lasers and lights was deployed from the NOAA research vessel Tatoosh during the month of September 2006 and...

  3. Robust video object cosegmentation.

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing; Li, Xuelong; Porikli, Fatih

    2015-10-01

    With ever-increasing volumes of video data, automatic extraction of salient object regions became even more significant for visual analytic solutions. This surge has also opened up opportunities for taking advantage of collective cues encapsulated in multiple videos in a cooperative manner. However, it also brings up major challenges, such as handling of drastic appearance, motion pattern, and pose variations, of foreground objects as well as indiscriminate backgrounds. Here, we present a cosegmentation framework to discover and segment out common object regions across multiple frames and multiple videos in a joint fashion. We incorporate three types of cues, i.e., intraframe saliency, interframe consistency, and across-video similarity into an energy optimization framework that does not make restrictive assumptions on foreground appearance and motion model, and does not require objects to be visible in all frames. We also introduce a spatio-temporal scale-invariant feature transform (SIFT) flow descriptor to integrate across-video correspondence from the conventional SIFT-flow into interframe motion flow from optical flow. This novel spatio-temporal SIFT flow generates reliable estimations of common foregrounds over the entire video data set. Experimental results show that our method outperforms the state-of-the-art on a new extensive data set (ViCoSeg).

  4. Video games

    OpenAIRE

    Kolář, Vojtěch

    2012-01-01

    This thesis is based on a detailed analysis of various topics related to the question of whether video games can be art. In the first place it analyzes the current academic discussion on this subject and confronts different opinions of both supporters and objectors of the idea, that video games can be a full-fledged art form. The second point of this paper is to analyze the properties, that are inherent to video games, in order to find the reason, why cultural elite considers video games as i...

  5. Deception Detection in Videos

    OpenAIRE

    Wu, Zhe; Singh, Bharat; Davis, Larry S.; Subrahmanian, V. S.

    2017-01-01

    We present a system for covert automated deception detection in real-life courtroom trial videos. We study the importance of different modalities like vision, audio and text for this task. On the vision side, our system uses classifiers trained on low level video features which predict human micro-expressions. We show that predictions of high-level micro-expressions can be used as features for deception prediction. Surprisingly, IDT (Improved Dense Trajectory) features which have been widely ...

  6. Contextual analysis of videos

    CERN Document Server

    Thida, Myo; Monekosso, Dorothy

    2013-01-01

    Video context analysis is an active and vibrant research area, which provides means for extracting, analyzing and understanding behavior of a single target and multiple targets. Over the last few decades, computer vision researchers have been working to improve the accuracy and robustness of algorithms to analyse the context of a video automatically. In general, the research work in this area can be categorized into three major topics: 1) counting number of people in the scene 2) tracking individuals in a crowd and 3) understanding behavior of a single target or multiple targets in the scene.

  7. Combining Position Weight Matrices and Document-Term Matrix for Efficient Extraction of Associations of Methylated Genes and Diseases from Free Text

    KAUST Repository

    Bin Raies, Arwa; Mansour, Hicham; Incitti, Roberto; Bajic, Vladimir B.

    2013-01-01

    implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually.Methodology:We developed a novel text mining methodology based on a new concept of position weight matrices

  8. Akademisk video

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2017-01-01

    Dette kapitel har fokus på metodiske problemstillinger, der opstår i forhold til at bruge (digital) video i forbindelse med forskningskommunikation, ikke mindst online. Video har længe været benyttet i forskningen til dataindsamling og forskningskommunikation. Med digitaliseringen og internettet ...

  9. Video Podcasts

    DEFF Research Database (Denmark)

    Nortvig, Anne Mette; Sørensen, Birgitte Holm

    2016-01-01

    This project’s aim was to support and facilitate master’s students’ preparation and collaboration by making video podcasts of short lectures available on YouTube prior to students’ first face-to-face seminar. The empirical material stems from group interviews, from statistical data created through...... YouTube analytics and from surveys answered by students after the seminar. The project sought to explore how video podcasts support learning and reflection online and how students use and reflect on the integration of online activities in the videos. Findings showed that students engaged actively...

  10. Video games.

    Science.gov (United States)

    Funk, Jeanne B

    2005-06-01

    The video game industry insists that it is doing everything possible to provide information about the content of games so that parents can make informed choices; however, surveys indicate that ratings may not reflect consumer views of the nature of the content. This article describes some of the currently popular video games, as well as developments that are on the horizon, and discusses the status of research on the positive and negative impacts of playing video games. Recommendations are made to help parents ensure that children play games that are consistent with their values.

  11. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... v/K5u3sb-Dbkc Watch additional videos about getting help. Behind the Scenes see more videos from Veterans Health Administration Be There: Help Save a Life see more videos from Veterans ...

  12. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... for help. Bittersweet More Videos from Veterans Health Administration Embedded YouTube video: https://www.youtube.com/v/ ... the Scenes see more videos from Veterans Health Administration Be There: Help Save a Life see more ...

  13. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... more videos from Veterans Health Administration Lost: The Power of One Connection see more videos from Veterans Health Administration The Power of 1 PSA see more videos from Veterans ...

  14. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... out for help. Bittersweet More Videos from Veterans Health Administration Embedded YouTube video: https://www.youtube.com/ ... Behind the Scenes see more videos from Veterans Health Administration Be There: Help Save a Life see ...

  15. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Videos Experiencing Celiac Disease What is Celiac Disease Diet Information At ... Us Celiac Disease Program | Videos Boston Children's Hospital will teach you and your family about a ...

  16. Video Comparator

    International Nuclear Information System (INIS)

    Rose, R.P.

    1978-01-01

    The Video Comparator is a comparative gage that uses electronic images from two sources, a standard and an unknown. Two matched video cameras are used to obtain the electronic images. The video signals are mixed and displayed on a single video receiver (CRT). The video system is manufactured by ITP of Chatsworth, CA and is a Tele-Microscope II, Model 148. One of the cameras is mounted on a toolmaker's microscope stand and produces a 250X image of a cast. The other camera is mounted on a stand and produces an image of a 250X template. The two video images are mixed in a control box provided by ITP and displayed on a CRT. The template or the cast can be moved to align the desired features. Vertical reference lines are provided on the CRT, and a feature on the cast can be aligned with a line on the CRT screen. The stage containing the casts can be moved using a Boeckleler micrometer equipped with a digital readout, and a second feature aligned with the reference line and the distance moved obtained from the digital display

  17. Automated Indexing and Search of Video Data in Large Collections with inVideo

    Directory of Open Access Journals (Sweden)

    Shuangbao Paul Wang

    2017-08-01

    Full Text Available In this paper, we present a novel system, inVideo, for automatically indexing and searching videos based on the keywords spoken in the audio track and the visual content of the video frames. Using the highly efficient video indexing engine we developed, inVideo is able to analyze videos using machine learning and pattern recognition without the need for initial viewing by a human. The time-stamped commenting and tagging features refine the accuracy of search results. The cloud-based implementation makes it possible to conduct elastic search, augmented search, and data analytics. Our research shows that inVideo presents an efficient tool in processing and analyzing videos and increasing interactions in video-based online learning environment. Data from a cybersecurity program with more than 500 students show that applying inVideo to current video material, interactions between student-student and student-faculty increased significantly across 24 sections program-wide.

  18. Knowledge-based approach to video content classification

    Science.gov (United States)

    Chen, Yu; Wong, Edward K.

    2001-01-01

    A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

  19. ABOUT SOUNDS IN VIDEO GAMES

    Directory of Open Access Journals (Sweden)

    Denikin Anton A.

    2012-12-01

    Full Text Available The article considers the aesthetical and practical possibilities for sounds (sound design in video games and interactive applications. Outlines the key features of the game sound, such as simulation, representativeness, interactivity, immersion, randomization, and audio-visuality. The author defines the basic terminology in study of game audio, as well as identifies significant aesthetic differences between film sounds and sounds in video game projects. It is an attempt to determine the techniques of art analysis for the approaches in study of video games including aesthetics of their sounds. The article offers a range of research methods, considering the video game scoring as a contemporary creative practice.

  20. Compact Visualisation of Video Summaries

    Directory of Open Access Journals (Sweden)

    Janko Ćalić

    2007-01-01

    Full Text Available This paper presents a system for compact and intuitive video summarisation aimed at both high-end professional production environments and small-screen portable devices. To represent large amounts of information in the form of a video key-frame summary, this paper studies the narrative grammar of comics, and using its universal and intuitive rules, lays out visual summaries in an efficient and user-centered way. In addition, the system exploits visual attention modelling and rapid serial visual presentation to generate highly compact summaries on mobile devices. A robust real-time algorithm for key-frame extraction is presented. The system ranks importance of key-frame sizes in the final layout by balancing the dominant visual representability and discovery of unanticipated content utilising a specific cost function and an unsupervised robust spectral clustering technique. A final layout is created using an optimisation algorithm based on dynamic programming. Algorithm efficiency and robustness are demonstrated by comparing the results with a manually labelled ground truth and with optimal panelling solutions.

  1. GPS-Aided Video Tracking

    Directory of Open Access Journals (Sweden)

    Udo Feuerhake

    2015-08-01

    Full Text Available Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS- and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.

  2. Robust Watermarking of Video Streams

    Directory of Open Access Journals (Sweden)

    T. Polyák

    2006-01-01

    Full Text Available In the past few years there has been an explosion in the use of digital video data. Many people have personal computers at home, and with the help of the Internet users can easily share video files on their computer. This makes possible the unauthorized use of digital media, and without adequate protection systems the authors and distributors have no means to prevent it.Digital watermarking techniques can help these systems to be more effective by embedding secret data right into the video stream. This makes minor changes in the frames of the video, but these changes are almost imperceptible to the human visual system. The embedded information can involve copyright data, access control etc. A robust watermark is resistant to various distortions of the video, so it cannot be removed without affecting the quality of the host medium. In this paper I propose a video watermarking scheme that fulfills the requirements of a robust watermark. 

  3. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Patients from Johns Hopkins Stategies to Increase your Level of Physical Activity Role of Body Weight in Osteoarthritis Educational Videos for Patients Rheumatoid Arthritis Educational Video Series Psoriatic Arthritis 101 2010 E.S.C.A.P.E. Study Patient Update Transitioning the JRA ...

  4. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... Amblyopia Listen NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract Convergence ... is maintained by the NEI Office of Science Communications, Public Liaison, and Education. Technical questions about this ...

  5. Towards a Video Passive Content Fingerprinting Method for Partial-Copy Detection Robust against Non-Simulated Attacks.

    Directory of Open Access Journals (Sweden)

    Zobeida Jezabel Guzman-Zavaleta

    Full Text Available Passive content fingerprinting is widely used for video content identification and monitoring. However, many challenges remain unsolved especially for partial-copies detection. The main challenge is to find the right balance between the computational cost of fingerprint extraction and fingerprint dimension, without compromising detection performance against various attacks (robustness. Fast video detection performance is desirable in several modern applications, for instance, in those where video detection involves the use of large video databases or in applications requiring real-time video detection of partial copies, a process whose difficulty increases when videos suffer severe transformations. In this context, conventional fingerprinting methods are not fully suitable to cope with the attacks and transformations mentioned before, either because the robustness of these methods is not enough or because their execution time is very high, where the time bottleneck is commonly found in the fingerprint extraction and matching operations. Motivated by these issues, in this work we propose a content fingerprinting method based on the extraction of a set of independent binary global and local fingerprints. Although these features are robust against common video transformations, their combination is more discriminant against severe video transformations such as signal processing attacks, geometric transformations and temporal and spatial desynchronization. Additionally, we use an efficient multilevel filtering system accelerating the processes of fingerprint extraction and matching. This multilevel filtering system helps to rapidly identify potential similar video copies upon which the fingerprint process is carried out only, thus saving computational time. We tested with datasets of real copied videos, and the results show how our method outperforms state-of-the-art methods regarding detection scores. Furthermore, the granularity of our method makes

  6. Automatic Story Segmentation for TV News Video Using Multiple Modalities

    Directory of Open Access Journals (Sweden)

    Émilie Dumont

    2012-01-01

    Full Text Available While video content is often stored in rather large files or broadcasted in continuous streams, users are often interested in retrieving only a particular passage on a topic of interest to them. It is, therefore, necessary to split video documents or streams into shorter segments corresponding to appropriate retrieval units. We propose here a method for the automatic segmentation of TV news videos into stories. A-multiple-descriptor based segmentation approach is proposed. The selected multimodal features are complementary and give good insights about story boundaries. Once extracted, these features are expanded with a local temporal context and combined by an early fusion process. The story boundaries are then predicted using machine learning techniques. We investigate the system by experiments conducted using TRECVID 2003 data and protocol of the story boundary detection task, and we show that the proposed approach outperforms the state-of-the-art methods while requiring a very small amount of manual annotation.

  7. Parkinson's Disease Videos

    Medline Plus

    Full Text Available ... Is Initiated After Diagnosis? CareMAP: When Is It Time to Get Help? Unconditional Love CareMAP: Rest and Sleep: ... CareMAP: Mealtime and Swallowing: Part 1 ... of books, fact sheets, videos, podcasts, and more. To get started, use the search feature or check ...

  8. Video processing project

    CSIR Research Space (South Africa)

    Globisch, R

    2009-03-01

    Full Text Available Video processing source code for algorithms and tools used in software media pipelines (e.g. image scalers, colour converters, etc.) The currently available source code is written in C++ with their associated libraries and DirectShow- Filters....

  9. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Provider Meet the Team Blog Articles & Stories News Provider Directory Donate Resources Links Videos Podcasts Webinars For the Media For Clinicians For Policymakers For Family Caregivers Glossary Sign Up for ... Us Provider Directory What Is Palliative Care Definition Disease Types ...

  10. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... 30041 770-205-8211 info@ANAUSA.org The world’s #1 acoustic neuroma resource Click to learn more... ... is acoustic neuroma? Diagnosing Symptoms Side Effects Keywords World Language Videos Questions to ask Choosing a healthcare ...

  11. Video Golf

    Science.gov (United States)

    1995-01-01

    George Nauck of ENCORE!!! invented and markets the Advanced Range Performance (ARPM) Video Golf System for measuring the result of a golf swing. After Nauck requested their assistance, Marshall Space Flight Center scientists suggested video and image processing/computing technology, and provided leads on commercial companies that dealt with the pertinent technologies. Nauck contracted with Applied Research Inc. to develop a prototype. The system employs an elevated camera, which sits behind the tee and follows the flight of the ball down range, catching the point of impact and subsequent roll. Instant replay of the video on a PC monitor at the tee allows measurement of the carry and roll. The unit measures distance and deviation from the target line, as well as distance from the target when one is selected. The information serves as an immediate basis for making adjustments or as a record of skill level progress for golfers.

  12. A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos.

    Science.gov (United States)

    Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

    2016-04-01

    Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today's keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users' information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively.ResultsThe authors produced a prototype implementation of the proposed system, which is publicly accessible athttps://patentq.njit.edu/oer To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable

  13. Digital video recording and archiving in ophthalmic surgery

    Directory of Open Access Journals (Sweden)

    Raju Biju

    2006-01-01

    Full Text Available Currently most ophthalmic operating rooms are equipped with an analog video recording system [analog Charge Couple Device camera for video grabbing and a Video Cassette Recorder for recording]. We discuss the various advantages of a digital video capture device, its archiving capabilities and our experience during the transition from analog to digital video recording and archiving. The basic terminology and concepts related to analog and digital video, along with the choice of hardware, software and formats for archiving are discussed.

  14. Detection of goal events in soccer videos

    Science.gov (United States)

    Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

    2005-01-01

    In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

  15. OAS :: Videos

    Science.gov (United States)

    subscriptions Videos Photos Live Webcast Social Media Facebook @oasofficial Facebook Twitter @oas_official Audios Photos Social Media Facebook Twitter Newsletters Press and Communications Department Contact us at Rights Actions against Corruption C Children Civil Registry Civil Society Contact Us Culture Cyber

  16. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... the special health problems and requirements of the blind.” News & Events Events Calendar NEI Press Releases News ... Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract Convergence Insufficiency Diabetic Eye Disease Dilated Eye ...

  17. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... and what other conditions are associated with RA. Learning more about your condition will allow you to ... Arthritis Educational Video Series Psoriatic Arthritis 101 2010 E.S.C.A.P.E. Study Patient Update Transitioning ...

  18. NEI You Tube Videos: Amblyopia

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    Full Text Available ... Diabetic Eye Disease Education Program Glaucoma Education Program Low Vision Education Program Hispanic/Latino Program Vision and Aging ... Kids Glaucoma Healthy Vision Tips Leber Congenital Amaurosis Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos ...

  19. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... and Aging Program African American Program Training and Jobs Fellowships NEI Summer Intern Program Diversity In Vision ... DIVRO) Student Training Programs To search for current job openings visit HHS USAJobs Home >> NEI YouTube Videos >> ...

  20. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... to take a more active role in your care. The information in these videos should not take ... She is a critical member of our patient care team. Managing Your Arthritis Managing Your Arthritis Managing ...

  1. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... a more active role in your care. The information in these videos should not take the place of any advice you ... Management for Rheumatoid Arthritis Patients Rehabilitation of Older Adult ...

  2. TACKLING EVENT DETECTION IN THE CONTEXT OF VIDEO SURVEILLANCE

    Directory of Open Access Journals (Sweden)

    Raducu DUMITRESCU

    2011-11-01

    Full Text Available In this paper we address the problem of event detection in the context of video surveillance systems. First we deal with background extraction. Three methods are being tested, namely: frame differencing, running average and an estimate of median filtering technique. This provides information about changing contents. Further, we use this information to address human presence detection in the scene. This is carried out thought a contour-based approach. Contours are extracted from moving regions and parameterized. Human silhouettes show particular signatures of these parameters. Experimental results prove the potential of this approach to event detection. However, these are our first preliminary results to this application.

  3. Extracting Conceptual Feature Structures from Text

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik; Lassen, Tine

    2011-01-01

    and mapped into concepts in a generative ontology. Synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well...

  4. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... Health Growth & Development Infections Diseases & Conditions Pregnancy & Baby Nutrition & Fitness Emotions & Behavior School & Family Life First Aid & Safety Doctors & Hospitals Videos ...

  5. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Parents site Sitio para padres General Health Growth & Development Infections Diseases ... Special Needs: Planning for Adulthood (Video) KidsHealth / For Parents / Special Needs: ...

  6. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... Development Infections Diseases & Conditions Pregnancy & Baby Nutrition & Fitness Emotions & Behavior School & Family Life First Aid & Safety Doctors & Hospitals Videos Recipes ...

  7. A Secure and Robust Object-Based Video Authentication System

    Directory of Open Access Journals (Sweden)

    He Dajun

    2004-01-01

    Full Text Available An object-based video authentication system, which combines watermarking, error correction coding (ECC, and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI.

  8. Intelligent Model for Video Survillance Security System

    Directory of Open Access Journals (Sweden)

    J. Vidhya

    2013-12-01

    Full Text Available Video surveillance system senses and trails out all the threatening issues in the real time environment. It prevents from security threats with the help of visual devices which gather the information related to videos like CCTV’S and IP (Internet Protocol cameras. Video surveillance system has become a key for addressing problems in the public security. They are mostly deployed on the IP based network. So, all the possible security threats exist in the IP based application might also be the threats available for the reliable application which is available for video surveillance. In result, it may increase cybercrime, illegal video access, mishandling videos and so on. Hence, in this paper an intelligent model is used to propose security for video surveillance system which ensures safety and it provides secured access on video.

  9. Performance Analysis of Video Transmission Using Sequential Distortion Minimization Method for Digital Video Broadcasting Terrestrial

    Directory of Open Access Journals (Sweden)

    Novita Astin

    2016-12-01

    Full Text Available This paper presents about the transmission of Digital Video Broadcasting system with streaming video resolution 640x480 on different IQ rate and modulation. In the video transmission, distortion often occurs, so the received video has bad quality. Key frames selection algorithm is flexibel on a change of video, but on these methods, the temporal information of a video sequence is omitted. To minimize distortion between the original video and received video, we aimed at adding methodology using sequential distortion minimization algorithm. Its aim was to create a new video, better than original video without significant loss of content between the original video and received video, fixed sequentially. The reliability of video transmission was observed based on a constellation diagram, with the best result on IQ rate 2 Mhz and modulation 8 QAM. The best video transmission was also investigated using SEDIM (Sequential Distortion Minimization Method and without SEDIM. The experimental result showed that the PSNR (Peak Signal to Noise Ratio average of video transmission using SEDIM was an increase from 19,855 dB to 48,386 dB and SSIM (Structural Similarity average increase 10,49%. The experimental results and comparison of proposed method obtained a good performance. USRP board was used as RF front-end on 2,2 GHz.

  10. SIRSALE: integrated video database management tools

    Science.gov (United States)

    Brunie, Lionel; Favory, Loic; Gelas, J. P.; Lefevre, Laurent; Mostefaoui, Ahmed; Nait-Abdesselam, F.

    2002-07-01

    Video databases became an active field of research during the last decade. The main objective in such systems is to provide users with capabilities to friendly search, access and playback distributed stored video data in the same way as they do for traditional distributed databases. Hence, such systems need to deal with hard issues : (a) video documents generate huge volumes of data and are time sensitive (streams must be delivered at a specific bitrate), (b) contents of video data are very hard to be automatically extracted and need to be humanly annotated. To cope with these issues, many approaches have been proposed in the literature including data models, query languages, video indexing etc. In this paper, we present SIRSALE : a set of video databases management tools that allow users to manipulate video documents and streams stored in large distributed repositories. All the proposed tools are based on generic models that can be customized for specific applications using ad-hoc adaptation modules. More precisely, SIRSALE allows users to : (a) browse video documents by structures (sequences, scenes, shots) and (b) query the video database content by using a graphical tool, adapted to the nature of the target video documents. This paper also presents an annotating interface which allows archivists to describe the content of video documents. All these tools are coupled to a video player integrating remote VCR functionalities and are based on active network technology. So, we present how dedicated active services allow an optimized video transport for video streams (with Tamanoir active nodes). We then describe experiments of using SIRSALE on an archive of news video and soccer matches. The system has been demonstrated to professionals with a positive feedback. Finally, we discuss open issues and present some perspectives.

  11. A blind video watermarking scheme resistant to rotation and collusion attacks

    Directory of Open Access Journals (Sweden)

    Amlan Karmakar

    2016-04-01

    Full Text Available In this paper, Discrete Cosine Transform (DCT based blind video watermarking algorithm is proposed, which is perceptually invisible and robust against rotation and collusion attacks. To make the scheme resistant against rotation, watermark is embedded within the square blocks, placed on the middle position of every luminance channel. Then Zernike moments of those square blocks are calculated. The rotation invariance property of the Complex Zernike moments is exploited to predict the rotation angle of the video at the time of extraction of watermark bits. To make the scheme robust against collusion, design of the scheme is done in such a way that the embedding blocks will vary for the successive frames of the video. A Pseudo Random Number (PRN generator and a permutation vector are used to achieve the goal. The experimental results show that the scheme is robust against conventional video attacks, rotation attack and collusion attacks.

  12. Collection of regulatory texts relative to radiation protection. Part 1: laws and decrees (Extracts of the Public Health Code and of the Labour Code dealing with the protection of population, patients and workers against the hazards of ionizing radiations

    International Nuclear Information System (INIS)

    Rivas, Robert; Feries, Jean; Marzorati, Frank; Chevalier, Celine; Lachaume, Jean-Luc

    2013-01-01

    This first part contains legal and regulatory texts extracted from the Public Health Code and related to health general protection and to health products (medical devices), from the Social Security Code, and from the Labour Code related to individual work relationships, to health and safety at work, to work places, to work equipment and means of protection, to the prevention of some exposure risks and of risks related to some activities. This document is an update of the previous version from January 25, 2011

  13. Roadside video data analysis deep learning

    CERN Document Server

    Verma, Brijesh; Stockwell, David

    2017-01-01

    This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

  14. Visual hashing of digital video : applications and techniques

    NARCIS (Netherlands)

    Oostveen, J.; Kalker, A.A.C.M.; Haitsma, J.A.; Tescher, A.G.

    2001-01-01

    his paper present the concept of robust video hashing as a tool for video identification. We present considerations and a technique for (i) extracting essential perceptual features from a moving image sequences and (ii) for identifying any sufficiently long unknown video segment by efficiently

  15. Cobra: A content-based video retrieval system

    NARCIS (Netherlands)

    Petkovic, M.; Jonker, W.; Jensen, C.S.; Jeffery, K.G.; Pokorny, J.; Saltenis, S.; Bertino, E.; Böhm, K.; Jarke, M.

    2002-01-01

    An increasing number of large publicly available video libraries results in a demand for techniques that can manipulate the video data based on content. In this paper, we present a content-based video retrieval system called Cobra. The system supports automatic extraction and retrieval of high-level

  16. Problem with multi-video format M-learning applications

    CSIR Research Space (South Africa)

    Adeyeye, MO

    2014-01-01

    Full Text Available in conjunction with the technical aspects of video display in browsers, when varying media formats are used. The <video> tag used in this work renders videos from two sources with different MIME types. Feeds from the video sources, namely YouTube and UCT...

  17. Video Quality Prediction Models Based on Video Content Dynamics for H.264 Video over UMTS Networks

    Directory of Open Access Journals (Sweden)

    Asiya Khan

    2010-01-01

    Full Text Available The aim of this paper is to present video quality prediction models for objective non-intrusive, prediction of H.264 encoded video for all content types combining parameters both in the physical and application layer over Universal Mobile Telecommunication Systems (UMTS networks. In order to characterize the Quality of Service (QoS level, a learning model based on Adaptive Neural Fuzzy Inference System (ANFIS and a second model based on non-linear regression analysis is proposed to predict the video quality in terms of the Mean Opinion Score (MOS. The objective of the paper is two-fold. First, to find the impact of QoS parameters on end-to-end video quality for H.264 encoded video. Second, to develop learning models based on ANFIS and non-linear regression analysis to predict video quality over UMTS networks by considering the impact of radio link loss models. The loss models considered are 2-state Markov models. Both the models are trained with a combination of physical and application layer parameters and validated with unseen dataset. Preliminary results show that good prediction accuracy was obtained from both the models. The work should help in the development of a reference-free video prediction model and QoS control methods for video over UMTS networks.

  18. Using Video in the English Language Clasroom

    Directory of Open Access Journals (Sweden)

    Amado Vicente

    2002-08-01

    Full Text Available Video is a popular and a motivating potential medium in schools. Using video in the language classroom helps the language teachers in many different ways. Video, for instance, brings the outside world into the language classroom, providing the class with many different topics and reasons to talk about. It can provide comprehensible input to the learners through contextualised models of language use. It also offers good opportunities to introduce native English speech into the language classroom. Through this article I will try to show what the benefits of using video are and, at the end, I present an instrument to select and classify video materials.

  19. Keeping the Game Alive: Evaluating Strategies for the Preservation of Console Video Games

    Directory of Open Access Journals (Sweden)

    Mark Guttenbrunner

    2010-07-01

    Full Text Available Interactive fiction and video games are part of our cultural heritage. As original systems cease to work because of hardware and media failures, methods to preserve obsolete video games for future generations have to be developed. The public interest in early video games is high, as exhibitions, regular magazines on the topic and newspaper articles demonstrate. Moreover, games considered to be classic are rereleased for new generations of gaming hardware. However, with the rapid development of new computer systems, the way games look and are played changes constantly. When trying to preserve console video games one faces problems of classified development documentation, legal aspects and extracting the contents from original media like cartridges with special hardware. Furthermore, special controllers and non-digital items are used to extend the gaming experience making it difficult to preserve the look and feel of console video games.This paper discusses strategies for the digital preservation of console video games. After a short overview of console video game systems, there follows an introduction to digital preservation and related work in common strategies for digital preservation and preserving interactive art. Then different preservation strategies are described with a specific focus on emulation. Finally a case study on console video game preservation is shown which uses the Planets preservation planning approach for evaluating preservation strategies in a documented decision-making process. Experiments are carried out to compare different emulators as well as other approaches, first for a single console video game system, then for different console systems of the same era and finally for systems of all eras. Comparison and discussion of results show that, while emulation works very well in principle for early console video games, various problems exist for the general use as a digital preservation alternative. We show what future work

  20. Inclusion in the Workplace - Text Version | NREL

    Science.gov (United States)

    Careers » Inclusion in the Workplace - Text Version Inclusion in the Workplace - Text Version This is the text version for the Inclusion: Leading by Example video. I'm Martin Keller. I'm the NREL of the laboratory. Another very important element in inclusion is diversity. Because if we have a

  1. Video Game Accessibility: A Legal Approach

    Directory of Open Access Journals (Sweden)

    George Powers

    2015-02-01

    Full Text Available Video game accessibility may not seem of significance to some, and it may sound trivial to anyone who does not play video games. This assumption is false. With the digitalization of our culture, video games are an ever increasing part of our life. They contribute to peer to peer interactions, education, music and the arts. A video game can be created by hundreds of musicians and artists, and they can have production budgets that exceed modern blockbuster films. Inaccessible video games are analogous to movie theaters without closed captioning or accessible facilities. The movement to have accessible video games is small, unorganized and misdirected. Just like the other battles to make society accessible were accomplished through legislation and law, the battle for video game accessibility must be focused toward the law and not the market.

  2. Impairment-Factor-Based Audiovisual Quality Model for IPTV: Influence of Video Resolution, Degradation Type, and Content Type

    Directory of Open Access Journals (Sweden)

    Garcia MN

    2011-01-01

    Full Text Available This paper presents an audiovisual quality model for IPTV services. The model estimates the audiovisual quality of standard and high definition video as perceived by the user. The model is developed for applications such as network planning and packet-layer quality monitoring. It mainly covers audio and video compression artifacts and impairments due to packet loss. The quality tests conducted for model development demonstrate a mutual influence of the perceived audio and video quality, and the predominance of the video quality for the overall audiovisual quality. The balance between audio quality and video quality, however, depends on the content, the video format, and the audio degradation type. The proposed model is based on impairment factors which quantify the quality-impact of the different degradations. The impairment factors are computed from parameters extracted from the bitstream or packet headers. For high definition video, the model predictions show a correlation with unknown subjective ratings of 95%. For comparison, we have developed a more classical audiovisual quality model which is based on the audio and video qualities and their interaction. Both quality- and impairment-factor-based models are further refined by taking the content-type into account. At last, the different model variants are compared with modeling approaches described in the literature.

  3. Scene text recognition in mobile applications by character descriptor and structure configuration.

    Science.gov (United States)

    Yi, Chucai; Tian, Yingli

    2014-07-01

    Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

  4. Airborne Video Surveillance

    National Research Council Canada - National Science Library

    Blask, Steven

    2002-01-01

    The DARPA Airborne Video Surveillance (AVS) program was established to develop and promote technologies to make airborne video more useful, providing capabilities that achieve a UAV force multiplier...

  5. Physics and Video Analysis

    Science.gov (United States)

    Allain, Rhett

    2016-05-01

    We currently live in a world filled with videos. There are videos on YouTube, feature movies and even videos recorded with our own cameras and smartphones. These videos present an excellent opportunity to not only explore physical concepts, but also inspire others to investigate physics ideas. With video analysis, we can explore the fantasy world in science-fiction films. We can also look at online videos to determine if they are genuine or fake. Video analysis can be used in the introductory physics lab and it can even be used to explore the make-believe physics embedded in video games. This book covers the basic ideas behind video analysis along with the fundamental physics principles used in video analysis. The book also includes several examples of the unique situations in which video analysis can be used.

  6. A video authentication technique

    International Nuclear Information System (INIS)

    Johnson, C.S.

    1987-01-01

    Unattended video surveillance systems are particularly vulnerable to the substitution of false video images into the cable that connects the camera to the video recorder. New technology has made it practical to insert a solid state video memory into the video cable, freeze a video image from the camera, and hold this image as long as desired. Various techniques, such as line supervision and sync detection, have been used to detect video cable tampering. The video authentication technique described in this paper uses the actual video image from the camera as the basis for detecting any image substitution made during the transmission of the video image to the recorder. The technique, designed for unattended video systems, can be used for any video transmission system where a two-way digital data link can be established. The technique uses similar microprocessor circuitry at the video camera and at the video recorder to select sample points in the video image for comparison. The gray scale value of these points is compared at the recorder controller and if the values agree within limits, the image is authenticated. If a significantly different image was substituted, the comparison would fail at a number of points and the video image would not be authenticated. The video authentication system can run as a stand-alone system or at the request of another system

  7. Software Patching Lessons Learned - Video Text Version | Energy Systems

    Science.gov (United States)

    just looking at a clock and doing it on a rhythmic basis or even just outside of the standard, you analysis accuracy is difficult. And this is essentially the quality of what you're finding and how you that process. All right. Lesson number four. Asset analysis is complicated. This is essentially knowing

  8. 2017 Cybersecurity Workshop: Cross Cutting Panel - Video Text Version |

    Science.gov (United States)

    tell an audience - let's say you are doing a Ted X talk. You've been invited. And these people are kind , was at a reception the same day of his graduation. I think it's 1965, it's Berkeley. He comes out, and impact to the grid. Erfan Ibrahim: Wonderful. So I'll entertain two questions for the audience, and then

  9. 2017 Cybersecurity Workshop: Readouts from Working Groups - Video Text

    Science.gov (United States)

    applicability of artificial intelligence to search for cybersecurity gaps in our existing SKATA networks. Second primarily renewable that all back each other up; that are all highly intelligent, artificial intelligence we have in cyber security, digital technologies, artificial intelligence. We think that that would

  10. Hydrogen Infrastructure Testing and Research Facility Video (Text Version)

    Science.gov (United States)

    grid integration, continuous code improvement, fuel cell vehicle operation, and renewable hydrogen Systems Integration Facility or ESIF. Research projects including H2FIRST, component testing, hydrogen

  11. A methodology for semiautomatic taxonomy of concepts extraction from nuclear scientific documents using text mining techniques; Metodologia para extracao semiautomatica de uma taxonomia de conceitos a partir da producao cientifica da area nuclear utilizando tecnicas de mineracao de textos

    Energy Technology Data Exchange (ETDEWEB)

    Braga, Fabiane dos Reis

    2013-07-01

    This thesis presents a text mining method for semi-automatic extraction of taxonomy of concepts, from a textual corpus composed of scientific papers related to nuclear area. The text classification is a natural human practice and a crucial task for work with large repositories. The document clustering technique provides a logical and understandable framework that facilitates the organization, browsing and searching. Most clustering algorithms using the bag of words model to represent the content of a document. This model generates a high dimensionality of the data, ignores the fact that different words can have the same meaning and does not consider the relationship between them, assuming that words are independent of each other. The methodology presents a combination of a model for document representation by concepts with a hierarchical document clustering method using frequency of co-occurrence concepts and a technique for clusters labeling more representatives, with the objective of producing a taxonomy of concepts which may reflect a structure of the knowledge domain. It is hoped that this work will contribute to the conceptual mapping of scientific production of nuclear area and thus support the management of research activities in this area. (author)

  12. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... from Veterans Health Administration The Power of 1 PSA see more videos from Veterans Health Administration Commitments PSA see more videos from Veterans Health Administration The ...

  13. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... Resources Spread the Word Videos Homeless Resources Additional Information Make the Connection Get Help When To Call ... Suicide Spread the Word Videos Homeless Resources Additional Information Make the Connection Resource Locator If you or ...

  14. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... videos from Veterans Health Administration Talking About It Matters see more videos from Veterans Health Administration Stand ... Health Administration I am A Veteran Family/Friend Active Duty/Reserve and Guard Signs of Crisis Identifying ...

  15. Rare Disease Video Portal

    OpenAIRE

    Sánchez Bocanegra, Carlos Luis

    2011-01-01

    Rare Disease Video Portal (RD Video) is a portal web where contains videos from Youtube including all details from 12 channels of Youtube. Rare Disease Video Portal (RD Video) es un portal web que contiene los vídeos de Youtube incluyendo todos los detalles de 12 canales de Youtube. Rare Disease Video Portal (RD Video) és un portal web que conté els vídeos de Youtube i que inclou tots els detalls de 12 Canals de Youtube.

  16. THE DETERMINATION OF THE SHARPNESS DEPTH BORDERS AND CORRESPONDING PHOTOGRAPHY AND VIDEO RECORDING PARAMETERS FOR CONTEMPORARY VIDEO TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    E. G. Zaytseva

    2011-01-01

    Full Text Available The method of determination of the sharpness depth borders was improved for contemporary video technology. The computer programme for determination of corresponding video recording parameters was created.

  17. A Novel Quantum Video Steganography Protocol with Large Payload Based on MCQI Quantum Video

    Science.gov (United States)

    Qu, Zhiguo; Chen, Siyi; Ji, Sai

    2017-11-01

    As one of important multimedia forms in quantum network, quantum video attracts more and more attention of experts and scholars in the world. A secure quantum video steganography protocol with large payload based on the video strip encoding method called as MCQI (Multi-Channel Quantum Images) is proposed in this paper. The new protocol randomly embeds the secret information with the form of quantum video into quantum carrier video on the basis of unique features of video frames. It exploits to embed quantum video as secret information for covert communication. As a result, its capacity are greatly expanded compared with the previous quantum steganography achievements. Meanwhile, the new protocol also achieves good security and imperceptibility by virtue of the randomization of embedding positions and efficient use of redundant frames. Furthermore, the receiver enables to extract secret information from stego video without retaining the original carrier video, and restore the original quantum video as a follow. The simulation and experiment results prove that the algorithm not only has good imperceptibility, high security, but also has large payload.

  18. Deep Learning for Detection of Object-Based Forgery in Advanced Video

    Directory of Open Access Journals (Sweden)

    Ye Yao

    2017-12-01

    Full Text Available Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based forgery in the advanced video. The presented deep learning approach utilizes a convolutional neural network (CNN to automatically extract high-dimension features from the input image patches. Different from the traditional CNN models used in computer vision domain, we let video frames go through three preprocessing layers before being fed into our CNN model. They include a frame absolute difference layer to cut down temporal redundancy between video frames, a max pooling layer to reduce computational complexity of image convolution, and a high-pass filter layer to enhance the residual signal left by video forgery. In addition, an asymmetric data augmentation strategy has been established to get a similar number of positive and negative image patches before the training. The experiments have demonstrated that the proposed CNN-based model with the preprocessing layers has achieved excellent results.

  19. Video Game Training and the Reward System

    Directory of Open Access Journals (Sweden)

    Robert C. Lorenz

    2015-02-01

    Full Text Available Video games contain elaborate reinforcement and reward schedules that have the potential to maximize motivation. Neuroimaging studies suggest that video games might have an influence on the reward system. However, it is not clear whether reward-related properties represent a precondition, which biases an individual towards playing video games, or if these changes are the result of playing video games. Therefore, we conducted a longitudinal study to explore reward-related functional predictors in relation to video gaming experience as well as functional changes in the brain in response to video game training.Fifty healthy participants were randomly assigned to a video game training (TG or control group (CG. Before and after training/control period, functional magnetic resonance imaging (fMRI was conducted using a non-video game related reward task.At pretest, both groups showed strongest activation in ventral striatum (VS during reward anticipation. At posttest, the TG showed very similar VS activity compared to pretest. In the CG, the VS activity was significantly attenuated.This longitudinal study revealed that video game training may preserve reward responsiveness in the ventral striatum in a retest situation over time. We suggest that video games are able to keep striatal responses to reward flexible, a mechanism which might be of critical value for applications such as therapeutic cognitive training.

  20. Using video in teacher education

    Directory of Open Access Journals (Sweden)

    Jo Towers

    2007-06-01

    Full Text Available This paper draws on a research study of elementary- and secondary-route preservice teachers in a two-year, after-degree teacher preparation programme. The paper includes excerpts of classroom data, taken from the author’s own university classroom, demonstrating preservice teachers’ responses to carefully selected video extracts of children learning mathematics in a high-school class also taught by the author. The paper includes commentary on some of the advantages and limitations of video as a teaching tool, develops an argument for the increased use, in both preservice teacher education and inservice teacher professional development, of videotaped episodes that focus on the learners rather than on the classroom teacher, and explores the value of having the teacher whose classroom is featured on the videos present for the discussion of the episodes. The paper explores the potential offered by video material to foster the belief that teaching is a learning activity by (i refocusing attention on the learner rather than the teacher in the analysis of classroom practices, (ii raising awareness of the importance of reflective practice, and (iii providing a prompt for the imaginative rehearsal of action. Résumé : Le présent article se fonde sur une étude technique portant sur des stagiaires des niveaux primaire et secondaire dans un programme de préparation à l’enseignement de deux ans après l’obtention du diplôme. L’article comprend des extraits de données en salle de classe qui proviennent de la salle de classe de l’université de l’auteur même, illustrant les réponses des stagiaires à des extraits vidéo choisis avec soins, extraits portant su des enfants apprenant les mathématiques dans une classe du secondaire dont l’enseignant est l’auteur. L’article comporte des commentaires sur certains des avantages et limites du vidéo comme outil d’enseignement, il présente un argument pour l’augmentation accrue, à la

  1. Directed Activities Related to Text: Text Analysis and Text Reconstruction.

    Science.gov (United States)

    Davies, Florence; Greene, Terry

    This paper describes Directed Activities Related to Text (DART), procedures that were developed and are used in the Reading for Learning Project at the University of Nottingham (England) to enhance learning from texts and that fall into two broad categories: (1) text analysis procedures, which require students to engage in some form of analysis of…

  2. No-Reference Video Quality Assessment using MPEG Analysis

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

    2013-01-01

    We present a method for No-Reference (NR) Video Quality Assessment (VQA) for decoded video without access to the bitstream. This is achieved by extracting and pooling features from a NR image quality assessment method used frame by frame. We also present methods to identify the video coding...... and estimate the video coding parameters for MPEG-2 and H.264/AVC which can be used to improve the VQA. The analysis differs from most other video coding analysis methods since it is without access to the bitstream. The results show that our proposed method is competitive with other recent NR VQA methods...

  3. Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

    Directory of Open Access Journals (Sweden)

    Irfan Mehmood

    2014-09-01

    Full Text Available Wireless capsule endoscopy (WCE has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

  4. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Answers (Q&A) Staying Safe Videos for Educators Search English Español Special Needs: Planning for Adulthood (Video) ... Nondiscrimination Visit the Nemours Web site. Note: All information on KidsHealth® is for educational purposes only. For ...

  5. Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC

    Directory of Open Access Journals (Sweden)

    Sima Ahmadpour

    2017-01-01

    Full Text Available Designing an effective and high performance network requires an accurate characterization and modeling of network traffic. The modeling of video frame sizes is normally applied in simulation studies and mathematical analysis and generating streams for testing and compliance purposes. Besides, video traffic assumed as a major source of multimedia traffic in future heterogeneous network. Therefore, the statistical distribution of video data can be used as the inputs for performance modeling of networks. The finding of this paper comprises the theoretical definition of distribution which seems to be relevant to the video trace in terms of its statistical properties and finds the best distribution using both the graphical method and the hypothesis test. The data set used in this article consists of layered video traces generating from Scalable Video Codec (SVC video compression technique of three different movies.

  6. Quality of Experience Assessment of Video Quality in Social Clouds

    Directory of Open Access Journals (Sweden)

    Asif Ali Laghari

    2017-01-01

    Full Text Available Video sharing on social clouds is popular among the users around the world. High-Definition (HD videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS. Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE level of end users. To assess the QoE of video compression, we conducted subjective (QoE experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

  7. Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

    Directory of Open Access Journals (Sweden)

    Yuchou Chang

    2008-02-01

    Full Text Available Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

  8. Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

    Directory of Open Access Journals (Sweden)

    Hong Yi

    2008-01-01

    Full Text Available Abstract Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

  9. A Customizable Text Classifier for Text Mining

    Directory of Open Access Journals (Sweden)

    Yun-liang Zhang

    2007-12-01

    Full Text Available Text mining deals with complex and unstructured texts. Usually a particular collection of texts that is specified to one or more domains is necessary. We have developed a customizable text classifier for users to mine the collection automatically. It derives from the sentence category of the HNC theory and corresponding techniques. It can start with a few texts, and it can adjust automatically or be adjusted by user. The user can also control the number of domains chosen and decide the standard with which to choose the texts based on demand and abundance of materials. The performance of the classifier varies with the user's choice.

  10. Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

    Directory of Open Access Journals (Sweden)

    Seymour Rowan

    2008-01-01

    Full Text Available Abstract We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

  11. Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

    Directory of Open Access Journals (Sweden)

    Ji Ming

    2008-03-01

    Full Text Available We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

  12. Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course

    Directory of Open Access Journals (Sweden)

    Michail N. Giannakos

    2015-02-01

    Full Text Available Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may provide insights into student learning performance and inform the improvement of video-assisted teaching tactics. Nevertheless, video analytics are not accessible to learning stakeholders, such as researchers and educators, mainly because online video platforms do not broadly share the interactions of the users with their systems. For this purpose, we have designed an open-access video analytics system for use in a video-assisted course. In this paper, we present a longitudinal study, which provides valuable insights through the lens of the collected video analytics. In particular, we found that there is a relationship between video navigation (repeated views and the level of cognition/thinking required for a specific video segment. Our results indicated that learning performance progress was slightly improved and stabilized after the third week of the video-assisted course. We also found that attitudes regarding easiness, usability, usefulness, and acceptance of this type of course remained at the same levels throughout the course. Finally, we triangulate analytics from diverse sources, discuss them, and provide the lessons learned for further development and refinement of video-assisted courses and practices.

  13. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... treatments are available, what is happening in the immune system and what other conditions are associated with RA. Learning more about your condition will allow you to take a more active role in your care. The information in these videos ...

  14. NEI You Tube Videos: Amblyopia

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    Full Text Available ... Program Vision and Aging Program African American Program Training and Jobs Fellowships NEI Summer Intern Program Diversity In Vision Research & Ophthalmology (DIVRO) Student Training Programs To search for current job openings visit HHS USAJobs Home >> NEI YouTube Videos >> ...

  15. NEI You Tube Videos: Amblyopia

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    Full Text Available ... and Aging Program African American Program Training and Jobs Fellowships NEI Summer Intern Program Diversity In Vision ... DIVRO) Student Training Programs To search for current job openings visit HHS USAJobs Home » NEI YouTube Videos » ...

  16. NEI You Tube Videos: Amblyopia

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    Full Text Available ... Macular Degeneration Amblyopia Animations Blindness Cataract Convergence Insufficiency Diabetic Eye Disease Dilated Eye Exam Dry Eye For Kids Glaucoma Healthy Vision Tips Leber Congenital Amaurosis Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube ...

  17. Video nueva herramienta del campo

    Directory of Open Access Journals (Sweden)

    Manuel Calvelo Ríos

    2015-01-01

    Full Text Available El Video resulta ser una herramienta sumamente útil para el desarrollo rural. Entendemos por desarrollo rural el intento de regular las relaciones campo-ciudad en términos más equitativos para el hombre del campo. Es por tanto una decisión política.

  18. NEI You Tube Videos: Amblyopia

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    Full Text Available ... Program Vision and Aging Program African American Program Training and Jobs Fellowships NEI Summer Intern Program Diversity In Vision Research & Ophthalmology (DIVRO) Student Training Programs To search for current job openings visit HHS USAJobs Home » NEI YouTube Videos » ...

  19. Video Classification and Adaptive QoP/QoS Control for Multiresolution Video Applications on IPTV

    Directory of Open Access Journals (Sweden)

    Huang Shyh-Fang

    2012-01-01

    Full Text Available With the development of heterogeneous networks and video coding standards, multiresolution video applications over networks become important. It is critical to ensure the service quality of the network for time-sensitive video services. Worldwide Interoperability for Microwave Access (WIMAX is a good candidate for delivering video signals because through WIMAX the delivery quality based on the quality-of-service (QoS setting can be guaranteed. The selection of suitable QoS parameters is, however, not trivial for service users. Instead, what a video service user really concerns with is the video quality of presentation (QoP which includes the video resolution, the fidelity, and the frame rate. In this paper, we present a quality control mechanism in multiresolution video coding structures over WIMAX networks and also investigate the relationship between QoP and QoS in end-to-end connections. Consequently, the video presentation quality can be simply mapped to the network requirements by a mapping table, and then the end-to-end QoS is achieved. We performed experiments with multiresolution MPEG coding over WIMAX networks. In addition to the QoP parameters, the video characteristics, such as, the picture activity and the video mobility, also affect the QoS significantly.

  20. Video Vortex reader II: moving images beyond YouTube

    NARCIS (Netherlands)

    Lovink, G.; Somers Miles, R.

    2011-01-01

    Video Vortex Reader II is the Institute of Network Cultures' second collection of texts that critically explore the rapidly changing landscape of online video and its use. With the success of YouTube ('2 billion views per day') and the rise of other online video sharing platforms, the moving image

  1. Action recognition in depth video from RGB perspective: A knowledge transfer manner

    Science.gov (United States)

    Chen, Jun; Xiao, Yang; Cao, Zhiguo; Fang, Zhiwen

    2018-03-01

    Different video modal for human action recognition has becoming a highly promising trend in the video analysis. In this paper, we propose a method for human action recognition from RGB video to Depth video using domain adaptation, where we use learned feature from RGB videos to do action recognition for depth videos. More specifically, we make three steps for solving this problem in this paper. First, different from image, video is more complex as it has both spatial and temporal information, in order to better encode this information, dynamic image method is used to represent each RGB or Depth video to one image, based on this, most methods for extracting feature in image can be used in video. Secondly, as video can be represented as image, so standard CNN model can be used for training and testing for videos, beside, CNN model can be also used for feature extracting as its powerful feature expressing ability. Thirdly, as RGB videos and Depth videos are belong to two different domains, in order to make two different feature domains has more similarity, domain adaptation is firstly used for solving this problem between RGB and Depth video, based on this, the learned feature from RGB video model can be directly used for Depth video classification. We evaluate the proposed method on one complex RGB-D action dataset (NTU RGB-D), and our method can have more than 2% accuracy improvement using domain adaptation from RGB to Depth action recognition.

  2. Video Browsing on Handheld Devices

    Science.gov (United States)

    Hürst, Wolfgang

    Recent improvements in processing power, storage space, and video codec development enable users now to playback video on their handheld devices in a reasonable quality. However, given the form factor restrictions of such a mobile device, screen size still remains a natural limit and - as the term "handheld" implies - always will be a critical resource. This is not only true for video but any data that is processed on such devices. For this reason, developers have come up with new and innovative ways to deal with large documents in such limited scenarios. For example, if you look at the iPhone, innovative techniques such as flicking have been introduced to skim large lists of text (e.g. hundreds of entries in your music collection). Automatically adapting the zoom level to, for example, the width of table cells when double tapping on the screen enables reasonable browsing of web pages that have originally been designed for large, desktop PC sized screens. A multi touch interface allows you to easily zoom in and out of large text documents and images using two fingers. In the next section, we will illustrate that advanced techniques to browse large video files have been developed in the past years, as well. However, if you look at state-of-the-art video players on mobile devices, normally just simple, VCR like controls are supported (at least at the time of this writing) that only allow users to just start, stop, and pause video playback. If supported at all, browsing and navigation functionality is often restricted to simple skipping of chapters via two single buttons for backward and forward navigation and a small and thus not very sensitive timeline slider.

  3. Detection of Double-Compressed H.264/AVC Video Incorporating the Features of the String of Data Bits and Skip Macroblocks

    Directory of Open Access Journals (Sweden)

    Heng Yao

    2017-12-01

    Full Text Available Today’s H.264/AVC coded videos have a high quality, high data-compression ratio. They also have a strong fault tolerance, better network adaptability, and have been widely applied on the Internet. With the popularity of powerful and easy-to-use video editing software, digital videos can be tampered with in various ways. Therefore, the double compression in the H.264/AVC video can be used as a first step in the study of video-tampering forensics. This paper proposes a simple, but effective, double-compression detection method that analyzes the periodic features of the string of data bits (SODBs and the skip macroblocks (S-MBs for all I-frames and P-frames in a double-compressed H.264/AVC video. For a given suspicious video, the SODBs and S-MBs are extracted for each frame. Both features are then incorporated to generate one enhanced feature to represent the periodic artifact of the double-compressed video. Finally, a time-domain analysis is conducted to detect the periodicity of the features. The primary Group of Pictures (GOP size is estimated based on an exhaustive strategy. The experimental results demonstrate the efficacy of the proposed method.

  4. Recommendations for recognizing video events by concept vocabularies

    Science.gov (United States)

    2014-06-01

    represents a video in terms of low-level audiovisual features [16,38,50,35,15,19,37]. In general, these methods first extract from the video various types of...interpretable, but is also reported to outperform the state-of-the-art low-level audiovisual features in recognizing events [31,33]. Rather than training...concept detector accuracy. As a consequence, the vocabulary concepts do not necessarily have a semantic interpreta- tion needed to explain the video content

  5. ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

    Directory of Open Access Journals (Sweden)

    I Made Oka Widyantara

    2015-12-01

    Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG-DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views

  6. Video Design Games

    DEFF Research Database (Denmark)

    Smith, Rachel Charlotte; Christensen, Kasper Skov; Iversen, Ole Sejer

    We introduce Video Design Games to train educators in teaching design. The Video Design Game is a workshop format consisting of three rounds in which participants observe, reflect and generalize based on video snippets from their own practice. The paper reports on a Video Design Game workshop...... in which 25 educators as part of a digital fabrication and design program were able to critically reflect on their teaching practice....

  7. Celiac Family Health Education Video Series

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    Full Text Available ... Information At Home Shopping Cooking Gluten Free Baking School Eating Out Away From Home Emotional Adjustment Kids Speak Research and Innovation Contact Us Celiac Disease Program | Videos ...

  8. Celiac Family Health Education Video Series

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    Full Text Available ... Emotional Adjustment Kids Speak Research and Innovation Contact Us Celiac Disease Program | Videos Boston Children's Hospital will teach you and your family about a healthful celiac lifestyle. Education is key in making parents feel more at ...

  9. Celiac Family Health Education Video Series

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    Full Text Available ... Donate Pay Your Bill MyChildren's Patient Portal Celiac Disease Program Contact the Celiac Disease Program 1-617- ... Kids Speak Research and Innovation Contact Us Celiac Disease Program | Videos Boston Children's Hospital will teach you ...

  10. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Fitness Diseases & Conditions Infections Drugs & Alcohol School & ... and opportunities available to them. While you help your tween or teen plan for the future, watch this video series together to learn about everything ...

  11. Celiac Family Health Education Video Series

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    Full Text Available ... Disease Diet Information At Home Shopping Cooking Gluten Free Baking School Eating Out Away From Home Emotional Adjustment Kids Speak Research and Innovation Contact Us Celiac Disease Program | Videos ...

  12. Celiac Family Health Education Video Series

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    Full Text Available ... Videos Experiencing Celiac Disease What is Celiac Disease Diet Information At Home Shopping Cooking Gluten Free Baking ... What is Celiac Disease? : Diagnosis and treatment III. Diet Information : How to start and maintain a gluten- ...

  13. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available [Skip to Content] for Parents Parents site Sitio para padres General Health Growth & Development Infections Diseases & Conditions Pregnancy & Baby Nutrition & Fitness Emotions & Behavior School & Family Life First Aid & Safety Doctors & Hospitals Videos Recipes for Kids ...

  14. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Diseases & Conditions Pregnancy & Baby Nutrition & Fitness Emotions & Behavior School & Family Life First Aid & Safety Doctors & Hospitals Videos ... Health Food & Fitness Diseases & Conditions Infections Drugs & Alcohol School & Jobs Sports Expert Answers (Q&A) Staying Safe ...

  15. Celiac Family Health Education Video Series

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    Full Text Available ... Group Patient Resources Gluten Free Cookbooks Gluten Free Recipes Videos Experiencing Celiac Disease What is Celiac Disease Diet Information At Home Shopping Cooking Gluten Free Baking School Eating Out Away From ...

  16. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... them. While you help your tween or teen plan for the future, watch this video series together ... Care for Your Child With Special Needs Special Education: Getting Help for Your Child Words to Know ( ...

  17. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Food & Fitness Diseases & Conditions Infections Drugs & Alcohol School & Jobs Sports Expert Answers (Q&A) Staying Safe Videos ... everything from financial and health care benefits to employment and housing options. More on this topic for: ...

  18. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... video series together to learn about everything from financial and health care benefits to employment and housing options. More on this topic for: Parents Financial Planning for Kids With Special Needs Giving Teens ...

  19. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Conditions Pregnancy & Baby Nutrition & Fitness Emotions & Behavior School & Family Life First Aid & Safety Doctors & Hospitals Videos Recipes ... Care for Your Child With Special Needs Special Education: Getting Help for Your Child Words to Know ( ...

  20. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Food & Fitness Diseases & Conditions Infections Drugs & Alcohol School & Jobs Sports Expert Answers (Q&A) Staying Safe Videos ... Care for Your Child With Special Needs Special Education: Getting Help for Your Child Words to Know ( ...

  1. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... the future, watch this video series together to learn about everything from financial and health care benefits to employment ... Respite Care for Your Child With Special Needs Special Education: Getting Help for ...

  2. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Feelings Expert Answers Q&A Movies & More for Teens Teens site Sitio para adolescentes Body Mind Sexual Health ... to them. While you help your tween or teen plan for the future, watch this video series ...

  3. The Children's Video Marketplace.

    Science.gov (United States)

    Ducey, Richard V.

    This report examines a growing submarket, the children's video marketplace, which comprises broadcast, cable, and video programming for children 2 to 11 years old. A description of the tremendous growth in the availability and distribution of children's programming is presented, the economics of the children's video marketplace are briefly…

  4. Video Self-Modeling

    Science.gov (United States)

    Buggey, Tom; Ogle, Lindsey

    2012-01-01

    Video self-modeling (VSM) first appeared on the psychology and education stage in the early 1970s. The practical applications of VSM were limited by lack of access to tools for editing video, which is necessary for almost all self-modeling videos. Thus, VSM remained in the research domain until the advent of camcorders and VCR/DVD players and,…

  5. Film grain noise modeling in advanced video coding

    Science.gov (United States)

    Oh, Byung Tae; Kuo, C.-C. Jay; Sun, Shijun; Lei, Shawmin

    2007-01-01

    A new technique for film grain noise extraction, modeling and synthesis is proposed and applied to the coding of high definition video in this work. The film grain noise is viewed as a part of artistic presentation by people in the movie industry. On one hand, since the film grain noise can boost the natural appearance of pictures in high definition video, it should be preserved in high-fidelity video processing systems. On the other hand, video coding with film grain noise is expensive. It is desirable to extract film grain noise from the input video as a pre-processing step at the encoder and re-synthesize the film grain noise and add it back to the decoded video as a post-processing step at the decoder. Under this framework, the coding gain of the denoised video is higher while the quality of the final reconstructed video can still be well preserved. Following this idea, we present a method to remove film grain noise from image/video without distorting its original content. Besides, we describe a parametric model containing a small set of parameters to represent the extracted film grain noise. The proposed model generates the film grain noise that is close to the real one in terms of power spectral density and cross-channel spectral correlation. Experimental results are shown to demonstrate the efficiency of the proposed scheme.

  6. Practicality in Virtuality: Finding Student Meaning in Video Game Education

    Science.gov (United States)

    Barko, Timothy; Sadler, Troy D.

    2013-01-01

    This paper looks at the conceptual differences between video game learning and traditional classroom and laboratory learning. It explores the notion of virtual experience by comparing a commonly used high school laboratory protocol on DNA extraction with a similar experience provided by a biotechnology themed video game. When considered…

  7. Young Children's Analogical Problem Solving: Gaining Insights from Video Displays

    Science.gov (United States)

    Chen, Zhe; Siegler, Robert S.

    2013-01-01

    This study examined how toddlers gain insights from source video displays and use the insights to solve analogous problems. Two- to 2.5-year-olds viewed a source video illustrating a problem-solving strategy and then attempted to solve analogous problems. Older but not younger toddlers extracted the problem-solving strategy depicted in the video…

  8. Summarization of Surveillance Video Sequences Using Face Quality Assessment

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.; Rahmati, Mohammad

    2011-01-01

    Constant working surveillance cameras in public places, such as airports and banks, produce huge amount of video data. Faces in such videos can be extracted in real time. However, most of these detected faces are either redundant or useless. Redundant information adds computational costs to facial...

  9. Video-Aided GPS/INS Positioning and Attitude Determination

    National Research Council Canada - National Science Library

    Brown, Alison; Silva, Randy

    2006-01-01

    ... precise positioning and attitude information to be maintained, even during periods of extended GPS dropouts. This relies on information extracted from the video images of reference points and features to continue to update the inertial navigation solution. In this paper, the principles of the video-update method aredescribed.

  10. Text Maps: Helping Students Navigate Informational Texts.

    Science.gov (United States)

    Spencer, Brenda H.

    2003-01-01

    Notes that a text map is an instructional approach designed to help students gain fluency in reading content area materials. Discusses how the goal is to teach students about the important features of the material and how the maps can be used to build new understandings. Presents the procedures for preparing and using a text map. (SG)

  11. Selecting salient frames for spatiotemporal video modeling and segmentation.

    Science.gov (United States)

    Song, Xiaomu; Fan, Guoliang

    2007-12-01

    We propose a new statistical generative model for spatiotemporal video segmentation. The objective is to partition a video sequence into homogeneous segments that can be used as "building blocks" for semantic video segmentation. The baseline framework is a Gaussian mixture model (GMM)-based video modeling approach that involves a six-dimensional spatiotemporal feature space. Specifically, we introduce the concept of frame saliency to quantify the relevancy of a video frame to the GMM-based spatiotemporal video modeling. This helps us use a small set of salient frames to facilitate the model training by reducing data redundancy and irrelevance. A modified expectation maximization algorithm is developed for simultaneous GMM training and frame saliency estimation, and the frames with the highest saliency values are extracted to refine the GMM estimation for video segmentation. Moreover, it is interesting to find that frame saliency can imply some object behaviors. This makes the proposed method also applicable to other frame-related video analysis tasks, such as key-frame extraction, video skimming, etc. Experiments on real videos demonstrate the effectiveness and efficiency of the proposed method.

  12. VBR video traffic models

    CERN Document Server

    Tanwir, Savera

    2014-01-01

    There has been a phenomenal growth in video applications over the past few years. An accurate traffic model of Variable Bit Rate (VBR) video is necessary for performance evaluation of a network design and for generating synthetic traffic that can be used for benchmarking a network. A large number of models for VBR video traffic have been proposed in the literature for different types of video in the past 20 years. Here, the authors have classified and surveyed these models and have also evaluated the models for H.264 AVC and MVC encoded video and discussed their findings.

  13. Intelligent video surveillance systems

    CERN Document Server

    Dufour, Jean-Yves

    2012-01-01

    Belonging to the wider academic field of computer vision, video analytics has aroused a phenomenal surge of interest since the current millennium. Video analytics is intended to solve the problem of the incapability of exploiting video streams in real time for the purpose of detection or anticipation. It involves analyzing the videos using algorithms that detect and track objects of interest over time and that indicate the presence of events or suspect behavior involving these objects.The aims of this book are to highlight the operational attempts of video analytics, to identify possi

  14. Error Resilient Video Compression Using Behavior Models

    Directory of Open Access Journals (Sweden)

    Jacco R. Taal

    2004-03-01

    Full Text Available Wireless and Internet video applications are inherently subjected to bit errors and packet errors, respectively. This is especially so if constraints on the end-to-end compression and transmission latencies are imposed. Therefore, it is necessary to develop methods to optimize the video compression parameters and the rate allocation of these applications that take into account residual channel bit errors. In this paper, we study the behavior of a predictive (interframe video encoder and model the encoders behavior using only the statistics of the original input data and of the underlying channel prone to bit errors. The resulting data-driven behavior models are then used to carry out group-of-pictures partitioning and to control the rate of the video encoder in such a way that the overall quality of the decoded video with compression and channel errors is optimized.

  15. Flip Video for Dummies

    CERN Document Server

    Hutsko, Joe

    2010-01-01

    The full-color guide to shooting great video with the Flip Video camera. The inexpensive Flip Video camera is currently one of the hottest must-have gadgets. It's portable and connects easily to any computer to transfer video you shoot onto your PC or Mac. Although the Flip Video camera comes with a quick-start guide, it lacks a how-to manual, and this full-color book fills that void! Packed with full-color screen shots throughout, Flip Video For Dummies shows you how to shoot the best possible footage in a variety of situations. You'll learn how to transfer video to your computer and then edi

  16. Text mining by Tsallis entropy

    Science.gov (United States)

    Jamaati, Maryam; Mehri, Ali

    2018-01-01

    Long-range correlations between the elements of natural languages enable them to convey very complex information. Complex structure of human language, as a manifestation of natural languages, motivates us to apply nonextensive statistical mechanics in text mining. Tsallis entropy appropriately ranks the terms' relevance to document subject, taking advantage of their spatial correlation length. We apply this statistical concept as a new powerful word ranking metric in order to extract keywords of a single document. We carry out an experimental evaluation, which shows capability of the presented method in keyword extraction. We find that, Tsallis entropy has reliable word ranking performance, at the same level of the best previous ranking methods.

  17. Towards a typology of video game trailers: Between the ludic and the cinematic

    Directory of Open Access Journals (Sweden)

    Jan Švelch

    2015-09-01

    Full Text Available This paper explores video game trailers, their various forms and the roles they play within video game industry and culture. It offers an overview of the current practice of video game trailer differentiation and proposes a new typology of video game trailers based on their relation to ludic and cinematic aspects of a video game, combining the theory of paratexts, video game performance framework, the interface effect concept, as well as the concept of transmedia storytelling. This typology reflects the historical evolution of a video game trailer and also takes into account current trends in the audiovisual paratexts of video games.

  18. 4K Video Traffic Prediction using Seasonal Autoregressive Modeling

    Directory of Open Access Journals (Sweden)

    D. R. Marković

    2017-06-01

    Full Text Available From the perspective of average viewer, high definition video streams such as HD (High Definition and UHD (Ultra HD are increasing their internet presence year over year. This is not surprising, having in mind expansion of HD streaming services, such as YouTube, Netflix etc. Therefore, high definition video streams are starting to challenge network resource allocation with their bandwidth requirements and statistical characteristics. Need for analysis and modeling of this demanding video traffic has essential importance for better quality of service and experience support. In this paper we use an easy-to-apply statistical model for prediction of 4K video traffic. Namely, seasonal autoregressive modeling is applied in prediction of 4K video traffic, encoded with HEVC (High Efficiency Video Coding. Analysis and modeling were performed within R programming environment using over 17.000 high definition video frames. It is shown that the proposed methodology provides good accuracy in high definition video traffic modeling.

  19. PERANCANGAN VIDEO PANDUAN FITNES SEBAGAI MEDIA PEMBELAJARAN

    Directory of Open Access Journals (Sweden)

    Rizkysari Meimaharani

    2013-06-01

    Full Text Available ABSTRACT Designing fitness exercise tutorial level beginner as learning and promotion media for life gym was designed to provide guidelines of good movement in the fitness training sessions for beginners, especially the gym because life member will be distributed free of charge for new members sign up. For the process of editing video tutorial software and hardware needed adequate for smooth production. The results also depend on the ability of either constituent knowledge of a general nature and especially directing, editing, creativity, and the ability of hardware, software and technology / computer. Excess video guide allows members to understand the movement is good and right to avoid unwanted injury. Not only guides the movement are presented in this video project but also the member is given petuntuk diet and proper diet for target practice can be easily achieved. Excess video guide allows members to understand the movement is good and right to avoid unwanted injury. Not only guides the movement are presented in this video project but also the member is given guide of diet and proper diet for target practice can be easily achieved. The presence of video editing technology offers convenience to an agency to educate the public through video learning and served as media promotion of a service or related agency theme of the video.

  20. The Aesthetics of the Ambient Video Experience

    Directory of Open Access Journals (Sweden)

    Jim Bizzocchi

    2008-01-01

    Full Text Available Ambient Video is an emergent cultural phenomenon, with roots that go deeply into the history of experimental film and video art. Ambient Video, like Brian Eno's ambient music, is video that "must be as easy to ignore as notice" [9]. This minimalist description conceals the formidable aesthetic challenge that faces this new form. Ambient video art works will hang on the walls of our living rooms, corporate offices, and public spaces. They will play in the background of our lives, living video paintings framed by the new generation of elegant, high-resolution flat-panel display units. However, they cannot command attention like a film or television show. They will patiently play in the background of our lives, yet they must always be ready to justify our attention in any given moment. In this capacity, ambient video works need to be equally proficient at rewarding a fleeting glance, a more direct look, or a longer contemplative gaze. This paper connects a series of threads that collectively illuminate the aesthetics of this emergent form: its history as a popular culture phenomenon, its more substantive artistic roots in avant-garde cinema and video art, its relationship to new technologies, the analysis of the viewer's conditions of reception, and the work of current artists who practice within this form.

  1. Video content analysis of surgical procedures.

    Science.gov (United States)

    Loukas, Constantinos

    2018-02-01

    In addition to its therapeutic benefits, minimally invasive surgery offers the potential for video recording of the operation. The videos may be archived and used later for reasons such as cognitive training, skills assessment, and workflow analysis. Methods from the major field of video content analysis and representation are increasingly applied in the surgical domain. In this paper, we review recent developments and analyze future directions in the field of content-based video analysis of surgical operations. The review was obtained from PubMed and Google Scholar search on combinations of the following keywords: 'surgery', 'video', 'phase', 'task', 'skills', 'event', 'shot', 'analysis', 'retrieval', 'detection', 'classification', and 'recognition'. The collected articles were categorized and reviewed based on the technical goal sought, type of surgery performed, and structure of the operation. A total of 81 articles were included. The publication activity is constantly increasing; more than 50% of these articles were published in the last 3 years. Significant research has been performed for video task detection and retrieval in eye surgery. In endoscopic surgery, the research activity is more diverse: gesture/task classification, skills assessment, tool type recognition, shot/event detection and retrieval. Recent works employ deep neural networks for phase and tool recognition as well as shot detection. Content-based video analysis of surgical operations is a rapidly expanding field. Several future prospects for research exist including, inter alia, shot boundary detection, keyframe extraction, video summarization, pattern discovery, and video annotation. The development of publicly available benchmark datasets to evaluate and compare task-specific algorithms is essential.

  2. Identifying hidden voice and video streams

    Science.gov (United States)

    Fan, Jieyan; Wu, Dapeng; Nucci, Antonio; Keralapura, Ram; Gao, Lixin

    2009-04-01

    Given the rising popularity of voice and video services over the Internet, accurately identifying voice and video traffic that traverse their networks has become a critical task for Internet service providers (ISPs). As the number of proprietary applications that deliver voice and video services to end users increases over time, the search for the one methodology that can accurately detect such services while being application independent still remains open. This problem becomes even more complicated when voice and video service providers like Skype, Microsoft, and Google bundle their voice and video services with other services like file transfer and chat. For example, a bundled Skype session can contain both voice stream and file transfer stream in the same layer-3/layer-4 flow. In this context, traditional techniques to identify voice and video streams do not work. In this paper, we propose a novel self-learning classifier, called VVS-I , that detects the presence of voice and video streams in flows with minimum manual intervention. Our classifier works in two phases: training phase and detection phase. In the training phase, VVS-I first extracts the relevant features, and subsequently constructs a fingerprint of a flow using the power spectral density (PSD) analysis. In the detection phase, it compares the fingerprint of a flow to the existing fingerprints learned during the training phase, and subsequently classifies the flow. Our classifier is not only capable of detecting voice and video streams that are hidden in different flows, but is also capable of detecting different applications (like Skype, MSN, etc.) that generate these voice/video streams. We show that our classifier can achieve close to 100% detection rate while keeping the false positive rate to less that 1%.

  3. An automatic analyzer for sports video databases using visual cues and real-world modeling

    NARCIS (Netherlands)

    Han, Jungong; Farin, D.S.; With, de P.H.N.; Lao, Weilun

    2006-01-01

    With the advent of hard-disk video recording, video databases gradually emerge for consumer applications. The large capacity of disks requires the need for fast storage and retrieval functions. We propose a semantic analyzer for sports video, which is able to automatically extract and analyze key

  4. Video-Stimulated Accounts: Young Children Accounting for Interactional Matters in Front of Peers

    Science.gov (United States)

    Theobald, Maryanne

    2012-01-01

    Research in the early years places increasing importance on participatory methods to engage children. The playback of video-recording to stimulate conversation is a research method that enables children's accounts to be heard and attends to a participatory view. During video-stimulated sessions, participants watch an extract of video-recording of…

  5. Video Toroid Cavity Imager

    Energy Technology Data Exchange (ETDEWEB)

    Gerald, Rex E. II; Sanchez, Jairo; Rathke, Jerome W.

    2004-08-10

    A video toroid cavity imager for in situ measurement of electrochemical properties of an electrolytic material sample includes a cylindrical toroid cavity resonator containing the sample and employs NMR and video imaging for providing high-resolution spectral and visual information of molecular characteristics of the sample on a real-time basis. A large magnetic field is applied to the sample under controlled temperature and pressure conditions to simultaneously provide NMR spectroscopy and video imaging capabilities for investigating electrochemical transformations of materials or the evolution of long-range molecular aggregation during cooling of hydrocarbon melts. The video toroid cavity imager includes a miniature commercial video camera with an adjustable lens, a modified compression coin cell imager with a fiat circular principal detector element, and a sample mounted on a transparent circular glass disk, and provides NMR information as well as a video image of a sample, such as a polymer film, with micrometer resolution.

  6. Digital Video in Research

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2012-01-01

    Is video becoming “the new black” in academia, if so, what are the challenges? The integration of video in research methodology (for collection, analysis) is well-known, but the use of “academic video” for dissemination is relatively new (Eriksson and Sørensen). The focus of this paper is academic......). In the video, I appear (along with other researchers) and two Danish film directors, and excerpts from their film. My challenges included how to edit the academic video and organize the collaborative effort. I consider video editing as a semiotic, transformative process of “reassembling” voices....... In the discussion, I review academic video in terms of relevance and implications for research practice. The theoretical background is social constructivist, combining social semiotics (Kress, van Leeuwen, McCloud), visual anthropology (Banks, Pink) and dialogic theory (Bakhtin). The Bakhtinian notion of “voices...

  7. Monitoring interaction and collective text production through text mining

    Directory of Open Access Journals (Sweden)

    Macedo, Alexandra Lorandi

    2014-04-01

    Full Text Available This article presents the Concepts Network tool, developed using text mining technology. The main objective of this tool is to extract and relate terms of greatest incidence from a text and exhibit the results in the form of a graph. The Network was implemented in the Collective Text Editor (CTE which is an online tool that allows the production of texts in synchronized or non-synchronized forms. This article describes the application of the Network both in texts produced collectively and texts produced in a forum. The purpose of the tool is to offer support to the teacher in managing the high volume of data generated in the process of interaction amongst students and in the construction of the text. Specifically, the aim is to facilitate the teacher’s job by allowing him/her to process data in a shorter time than is currently demanded. The results suggest that the Concepts Network can aid the teacher, as it provides indicators of the quality of the text produced. Moreover, messages posted in forums can be analyzed without their content necessarily having to be pre-read.

  8. Designing with video focusing the user-centred design process

    CERN Document Server

    Ylirisku, Salu Pekka

    2007-01-01

    Digital video for user-centered co-design is an emerging field of design, gaining increasing interest in both industry and academia. It merges the techniques and approaches of design ethnography, participatory design, interaction analysis, scenario-based design, and usability studies. This book covers the complete user-centered design project. It illustrates in detail how digital video can be utilized throughout the design process, from early user studies to making sense of video content and envisioning the future with video scenarios to provoking change with video artifacts. The text includes

  9. Video Encryption-A Survey

    OpenAIRE

    Jolly Shah; Vikas Saxena

    2011-01-01

    Multimedia data security is becoming important with the continuous increase of digital communications on internet. The encryption algorithms developed to secure text data are not suitable for multimedia application because of the large data size and real time constraint. In this paper, classification and description of various video encryption algorithms are presented. Analysis and Comparison of these algorithms with respect to various parameters like visual degradation, encryption ratio, spe...

  10. Sound for digital video

    CERN Document Server

    Holman, Tomlinson

    2013-01-01

    Achieve professional quality sound on a limited budget! Harness all new, Hollywood style audio techniques to bring your independent film and video productions to the next level.In Sound for Digital Video, Second Edition industry experts Tomlinson Holman and Arthur Baum give you the tools and knowledge to apply recent advances in audio capture, video recording, editing workflow, and mixing to your own film or video with stunning results. This fresh edition is chockfull of techniques, tricks, and workflow secrets that you can apply to your own projects from preproduction

  11. Learning Science Through Digital Video: Views on Watching and Creating Videos

    Science.gov (United States)

    Wade, P.; Courtney, A. R.

    2013-12-01

    In science, the use of digital video to document phenomena, experiments and demonstrations has rapidly increased during the last decade. The use of digital video for science education also has become common with the wide availability of video over the internet. However, as with using any technology as a teaching tool, some questions should be asked: What science is being learned from watching a YouTube clip of a volcanic eruption or an informational video on hydroelectric power generation? What are student preferences (e.g. multimedia versus traditional mode of delivery) with regard to their learning? This study describes 1) the efficacy of watching digital video in the science classroom to enhance student learning, 2) student preferences of instruction with regard to multimedia versus traditional delivery modes, and 3) the use of creating digital video as a project-based educational strategy to enhance learning. Undergraduate non-science majors were the primary focus group in this study. Students were asked to view video segments and respond to a survey focused on what they learned from the segments. Additionally, they were asked about their preference for instruction (e.g. text only, lecture-PowerPoint style delivery, or multimedia-video). A majority of students indicated that well-made video, accompanied with scientific explanations or demonstration of the phenomena was most useful and preferred over text-only or lecture instruction for learning scientific information while video-only delivery with little or no explanation was deemed not very useful in learning science concepts. The use of student generated video projects as learning vehicles for the creators and other class members as viewers also will be discussed.

  12. Wavelet-based audio embedding and audio/video compression

    Science.gov (United States)

    Mendenhall, Michael J.; Claypoole, Roger L., Jr.

    2001-12-01

    Watermarking, traditionally used for copyright protection, is used in a new and exciting way. An efficient wavelet-based watermarking technique embeds audio information into a video signal. Several effective compression techniques are applied to compress the resulting audio/video signal in an embedded fashion. This wavelet-based compression algorithm incorporates bit-plane coding, index coding, and Huffman coding. To demonstrate the potential of this audio embedding and audio/video compression algorithm, we embed an audio signal into a video signal and then compress. Results show that overall compression rates of 15:1 can be achieved. The video signal is reconstructed with a median PSNR of nearly 33 dB. Finally, the audio signal is extracted from the compressed audio/video signal without error.

  13. Electronic evaluation for video commercials by impression index.

    Science.gov (United States)

    Kong, Wanzeng; Zhao, Xinxin; Hu, Sanqing; Vecchiato, Giovanni; Babiloni, Fabio

    2013-12-01

    How to evaluate the effect of commercials is significantly important in neuromarketing. In this paper, we proposed an electronic way to evaluate the influence of video commercials on consumers by impression index. The impression index combines both the memorization and attention index during consumers observing video commercials by tracking the EEG activity. It extracts features from scalp EEG to evaluate the effectiveness of video commercials in terms of time-frequency-space domain. And, the general global field power was used as an impression index for evaluation of video commercial scenes as time series. Results of experiment demonstrate that the proposed approach is able to track variations of the cerebral activity related to cognitive task such as observing video commercials, and help to judge whether the scene in video commercials is impressive or not by EEG signals.

  14. Finding text in color images

    Science.gov (United States)

    Zhou, Jiangying; Lopresti, Daniel P.; Tasdizen, Tolga

    1998-04-01

    In this paper, we consider the problem of locating and extracting text from WWW images. A previous algorithm based on color clustering and connected components analysis works well as long as the color of each character is relatively uniform and the typography is fairly simple. It breaks down quickly, however, when these assumptions are violated. In this paper, we describe more robust techniques for dealing with this challenging problem. We present an improved color clustering algorithm that measures similarity based on both RGB and spatial proximity. Layout analysis is also incorporated to handle more complex typography. THese changes significantly enhance the performance of our text detection procedure.

  15. SparkText: Biomedical Text Mining on Big Data Framework.

    Directory of Open Access Journals (Sweden)

    Zhan Ye

    Full Text Available Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment.In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM, and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes.This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

  16. Drawing on Text Features for Reading Comprehension and Composing

    Science.gov (United States)

    Risko, Victoria J.; Walker-Dalhouse, Doris

    2011-01-01

    Students read multiple-genre texts such as graphic novels, poetry, brochures, digitized texts with videos, and informational and narrative texts. Features such as overlapping illustrations and implied cause-and-effect relationships can affect students' comprehension. Teaching with these texts and drawing attention to organizational features hold…

  17. Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

    Science.gov (United States)

    Lin, Sabrina; Fonteno, Shawn; Satish, Shruthi; Bhanu, Bir; Talbot, Prue

    2010-01-01

    Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion. PMID:20495527

  18. Text-Fabric

    NARCIS (Netherlands)

    Roorda, Dirk

    2016-01-01

    Text-Fabric is a Python3 package for Text plus Annotations. It provides a data model, a text file format, and a binary format for (ancient) text plus (linguistic) annotations. The emphasis of this all is on: data processing; sharing data; and contributing modules. A defining characteristic is that

  19. Contextual Text Mining

    Science.gov (United States)

    Mei, Qiaozhu

    2009-01-01

    With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the…

  20. XML and Free Text.

    Science.gov (United States)

    Riggs, Ken Roger

    2002-01-01

    Discusses problems with marking free text, text that is either natural language or semigrammatical but unstructured, that prevent well-formed XML from marking text for readily available meaning. Proposes a solution to mark meaning in free text that is consistent with the intended simplicity of XML versus SGML. (Author/LRW)

  1. SparkText: Biomedical Text Mining on Big Data Framework

    Science.gov (United States)

    He, Karen Y.; Wang, Kai

    2016-01-01

    Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

  2. SparkText: Biomedical Text Mining on Big Data Framework.

    Science.gov (United States)

    Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

    Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

  3. The Video Generation.

    Science.gov (United States)

    Provenzo, Eugene F., Jr.

    1992-01-01

    Video games are neither neutral nor harmless but represent very specific social and symbolic constructs. Research on the social content of today's video games reveals that sex bias and gender stereotyping are widely evident throughout the Nintendo games. Violence and aggression also pervade the great majority of the games. (MLF)

  4. Reviews in instructional video

    NARCIS (Netherlands)

    van der Meij, Hans

    2017-01-01

    This study investigates the effectiveness of a video tutorial for software training whose construction was based on a combination of insights from multimedia learning and Demonstration-Based Training. In the videos, a model of task performance was enhanced with instructional features that were

  5. Videos - The National Guard

    Science.gov (United States)

    Legislative Liaison Small Business Programs Social Media State Websites Videos Featured Videos On Every Front 2:17 Always Ready, Always There National Guard Bureau Diversity and Inclusion Play Button 1:04 National Guard Bureau Diversity and Inclusion The ChalleNGe Ep.5 [Graduation] Play Button 3:51 The

  6. Video Games as a Multifaceted Medium: A Review of Quantitative Social Science Research on Video Games and a Typology of Video Game Research Approaches

    Directory of Open Access Journals (Sweden)

    James D. Ivory

    2013-01-01

    Full Text Available Although there is a vast and useful body of quantitative social science research dealing with the social role and impact of video games, it is difficult to compare studies dealing with various dimensions of video games because they are informed by different perspectives and assumptions, employ different methodologies, and address different problems. Studies focusing on different social dimensions of video games can produce varied findings about games’ social function that are often difficult to reconcile— or even contradictory. Research is also often categorized by topic area, rendering a comprehensive view of video games’ social role across topic areas difficult. This interpretive review presents a novel typology of four identified approaches that categorize much of the quantitative social science video game research conducted to date: “video games as stimulus,” “video games as avocation,” “video games as skill,” and “video games as social environment.” This typology is useful because it provides an organizational structure within which the large and growing number of studies on video games can be categorized, guiding comparisons between studies on different research topics and aiding a more comprehensive understanding of video games’ social role. Categorizing the different approaches to video game research provides a useful heuristic for those critiquing and expanding that research, as well as an understandable entry point for scholars new to video game research. Further, and perhaps more importantly, the typology indicates when topics should be explored using different approaches than usual to shed new light on the topic areas. Lastly, the typology exposes the conceptual disconnects between the different approaches to video game research, allowing researchers to consider new ways to bridge gaps between the different approaches’ strengths and limitations with novel methods.

  7. Video Texture Synthesis Based on Flow-Like Stylization Painting

    Directory of Open Access Journals (Sweden)

    Qian Wenhua

    2014-01-01

    Full Text Available The paper presents an NP-video rendering system based on natural phenomena. It provides a simple nonphotorealistic video synthesis system in which user can obtain a flow-like stylization painting and infinite video scene. Firstly, based on anisotropic Kuwahara filtering in conjunction with line integral convolution, the phenomena video scene can be rendered to flow-like stylization painting. Secondly, the methods of frame division, patches synthesis, will be used to synthesize infinite playing video. According to selection examples from different natural video texture, our system can generate stylized of flow-like and infinite video scenes. The visual discontinuities between neighbor frames are decreased, and we also preserve feature and details of frames. This rendering system is easy and simple to implement.

  8. Rheumatoid Arthritis Educational Video Series

    Science.gov (United States)

    ... Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... Your Arthritis Managing Chronic Pain and Depression in Arthritis Nutrition & Rheumatoid Arthritis Arthritis and Health-related Quality of Life ...

  9. E-text

    DEFF Research Database (Denmark)

    Finnemann, Niels Ole

    2018-01-01

    text can be defined by taking as point of departure the digital format in which everything is represented in the binary alphabet. While the notion of text, in most cases, lends itself to be independent of medium and embodiment, it is also often tacitly assumed that it is, in fact, modeled around...... the print medium, rather than written text or speech. In late 20th century, the notion of text was subject to increasing criticism as in the question raised within literary text theory: is there a text in this class? At the same time, the notion was expanded by including extra linguistic sign modalities...

  10. Social video content delivery

    CERN Document Server

    Wang, Zhi; Zhu, Wenwu

    2016-01-01

    This brief presents new architecture and strategies for distribution of social video content. A primary framework for socially-aware video delivery and a thorough overview of the possible approaches is provided. The book identifies the unique characteristics of socially-aware video access and social content propagation, revealing the design and integration of individual modules that are aimed at enhancing user experience in the social network context. The change in video content generation, propagation, and consumption for online social networks, has significantly challenged the traditional video delivery paradigm. Given the massive amount of user-generated content shared in online social networks, users are now engaged as active participants in the social ecosystem rather than as passive receivers of media content. This revolution is being driven further by the deep penetration of 3G/4G wireless networks and smart mobile devices that are seamlessly integrated with online social networking and media-sharing s...

  11. Online video examination

    DEFF Research Database (Denmark)

    Qvist, Palle

    have large influence on their own teaching, learning and curriculum. The programme offers streamed videos in combination with other learning resources. It is a concept which offers video as pure presentation - video lectures - but also as an instructional tool which gives the students the possibility...... to construct their knowledge, collaboration and communication. In its first years the programme has used Skype video communication for collaboration and communication within and between groups, group members and their facilitators. Also exams have been mediated with the help of Skype and have for all students......, examiners and external examiners been a challenge and opportunity and has brought new knowledge and experience. This paper brings results from a questionnaire focusing on how the students experience the video examination....

  12. Automatic Association of Chats and Video Tracks for Activity Learning and Recognition in Aerial Video Surveillance

    Directory of Open Access Journals (Sweden)

    Riad I. Hammoud

    2014-10-01

    Full Text Available We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA and multi-media indexing and explorer (MINER. VIVA utilizes analyst call-outs (ACOs in the form of chat messages (voice-to-text to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter. MINER includes: (1 a fusion of graphical track and text data using probabilistic methods; (2 an activity pattern learning framework to support querying an index of activities of interest (AOIs and targets of interest (TOIs by movement type and geolocation; and (3 a user interface to support streaming multi-intelligence data processing. We also present an activity pattern learning framework that uses the multi-source associated data as training to index a large archive of full-motion videos (FMV. VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection/false alarm results due to the complexity of the scenario. The novel use of ACOs and chat Sensors 2014, 14 19844 messages in video tracking paves the way for user interaction, correction and preparation of situation awareness reports.

  13. A method of mobile video transmission based on J2ee

    Science.gov (United States)

    Guo, Jian-xin; Zhao, Ji-chun; Gong, Jing; Chun, Yang

    2013-03-01

    As 3G (3rd-generation) networks evolve worldwide, the rising demand for mobile video services and the enormous growth of video on the internet is creating major new revenue opportunities for mobile network operators and application developers. The text introduced a method of mobile video transmission based on J2ME, giving the method of video compressing, then describing the video compressing standard, and then describing the software design. The proposed mobile video method based on J2EE is a typical mobile multimedia application, which has a higher availability and a wide range of applications. The users can get the video through terminal devices such as phone.

  14. Texting on the Move

    Science.gov (United States)

    ... text. What's the Big Deal? The problem is multitasking. No matter how young and agile we are, ... on something other than the road. In fact, driving while texting (DWT) can be more dangerous than ...

  15. Surgical gesture classification from video and kinematic data.

    Science.gov (United States)

    Zappella, Luca; Béjar, Benjamín; Hager, Gregory; Vidal, René

    2013-10-01

    Much of the existing work on automatic classification of gestures and skill in robotic surgery is based on dynamic cues (e.g., time to completion, speed, forces, torque) or kinematic data (e.g., robot trajectories and velocities). While videos could be equally or more discriminative (e.g., videos contain semantic information not present in kinematic data), they are typically not used because of the difficulties associated with automatic video interpretation. In this paper, we propose several methods for automatic surgical gesture classification from video data. We assume that the video of a surgical task (e.g., suturing) has been segmented into video clips corresponding to a single gesture (e.g., grabbing the needle, passing the needle) and propose three methods to classify the gesture of each video clip. In the first one, we model each video clip as the output of a linear dynamical system (LDS) and use metrics in the space of LDSs to classify new video clips. In the second one, we use spatio-temporal features extracted from each video clip to learn a dictionary of spatio-temporal words, and use a bag-of-features (BoF) approach to classify new video clips. In the third one, we use multiple kernel learning (MKL) to combine the LDS and BoF approaches. Since the LDS approach is also applicable to kinematic data, we also use MKL to combine both types of data in order to exploit their complementarity. Our experiments on a typical surgical training setup show that methods based on video data perform equally well, if not better, than state-of-the-art approaches based on kinematic data. In turn, the combination of both kinematic and video data outperforms any other algorithm based on one type of data alone. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Text Coherence in Translation

    Science.gov (United States)

    Zheng, Yanping

    2009-01-01

    In the thesis a coherent text is defined as a continuity of senses of the outcome of combining concepts and relations into a network composed of knowledge space centered around main topics. And the author maintains that in order to obtain the coherence of a target language text from a source text during the process of translation, a translator can…

  17. Data Partitioning Technique for Improved Video Prioritization

    Directory of Open Access Journals (Sweden)

    Ismail Amin Ali

    2017-07-01

    Full Text Available A compressed video bitstream can be partitioned according to the coding priority of the data, allowing prioritized wireless communication or selective dropping in a congested channel. Known as data partitioning in the H.264/Advanced Video Coding (AVC codec, this paper introduces a further sub-partition of one of the H.264/AVC codec’s three data-partitions. Results show a 5 dB improvement in Peak Signal-to-Noise Ratio (PSNR through this innovation. In particular, the data partition containing intra-coded residuals is sub-divided into data from: those macroblocks (MBs naturally intra-coded, and those MBs forcibly inserted for non-periodic intra-refresh. Interactive user-to-user video streaming can benefit, as then HTTP adaptive streaming is inappropriate and the High Efficiency Video Coding (HEVC codec is too energy demanding.

  18. Turning Video Resource Management into Cloud Computing

    Directory of Open Access Journals (Sweden)

    Weili Kou

    2016-07-01

    Full Text Available Big data makes cloud computing more and more popular in various fields. Video resources are very useful and important to education, security monitoring, and so on. However, issues of their huge volumes, complex data types, inefficient processing performance, weak security, and long times for loading pose challenges in video resource management. The Hadoop Distributed File System (HDFS is an open-source framework, which can provide cloud-based platforms and presents an opportunity for solving these problems. This paper presents video resource management architecture based on HDFS to provide a uniform framework and a five-layer model for standardizing the current various algorithms and applications. The architecture, basic model, and key algorithms are designed for turning video resources into a cloud computing environment. The design was tested by establishing a simulation system prototype.

  19. THE EDUCATIONAL POTENTIAL OF VIDEO GAMES

    Directory of Open Access Journals (Sweden)

    Ruxandra Claudia CHIRCA (NEACȘU

    2015-11-01

    Full Text Available In nowadays' world, technological assistance is no longer confined to its primary purpose of communication or informational support and the boundaries between real and virtual world are becoming increasingly harder to be defined. This is the world of digital natives, today's children, who grow up in a technology-brimming environment and who spend most of their time playing video games. Are these video games constructive in any way? Scientific studies state they are. Video games help children in setting their goals, provide constant feedback and offer immediate rewards, along with the opportunity to collaborate with other players. Furthermore, video games can generate strong emotional reactions, such as joy or fear, and they have a captivating story line, which reveals itself within a realm of elaborate graphics.

  20. Efficient reversible data hiding in encrypted H.264/AVC videos

    Science.gov (United States)

    Xu, Dawen; Wang, Rangding

    2014-09-01

    Due to the security and privacy-preserving requirements for cloud data management, it is sometimes desired that video content is accessible in an encrypted form. Reversible data hiding in the encrypted domain is an emerging technology, as it can perform data hiding in encrypted videos without decryption, which preserves the confidentiality of the content. Furthermore, the original cover can be losslessly restored after decryption and data extraction. An efficient reversible data hiding scheme for encrypted H.264/AVC videos is proposed. During H.264/AVC encoding, the intraprediction mode, motion vector difference, and the sign bits of the residue coefficients are encrypted using a standard stream cipher. Then, the data-hider who does not know the original video content, may reversibly embed secret data into the encrypted H.264/AVC video by using a modified version of the histogram shifting technique. A scale factor is utilized for selecting the embedding zone, which is scalable for different capacity requirements. With an encrypted video containing hidden data, data extraction can be carried out either in the encrypted or decrypted domain. In addition, real reversibility is realized so that data extraction and video recovery are free of any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

  1. A text zero-watermarking method based on keyword dense interval

    Science.gov (United States)

    Yang, Fan; Zhu, Yuesheng; Jiang, Yifeng; Qing, Yin

    2017-07-01

    Digital watermarking has been recognized as a useful technology for the copyright protection and authentication of digital information. However, rarely did the former methods focus on the key content of digital carrier. The idea based on the protection of key content is more targeted and can be considered in different digital information, including text, image and video. In this paper, we use text as research object and a text zero-watermarking method which uses keyword dense interval (KDI) as the key content is proposed. First, we construct zero-watermarking model by introducing the concept of KDI and giving the method of KDI extraction. Second, we design detection model which includes secondary generation of zero-watermark and the similarity computing method of keyword distribution. Besides, experiments are carried out, and the results show that the proposed method gives better performance than other available methods especially in the attacks of sentence transformation and synonyms substitution.

  2. A new video programme

    CERN Multimedia

    CERN video productions

    2011-01-01

    "What's new @ CERN?", a new monthly video programme, will be broadcast on the Monday of every month on webcast.cern.ch. Aimed at the general public, the programme will cover the latest CERN news, with guests and explanatory features. Tune in on Monday 3 October at 4 pm (CET) to see the programme in English, and then at 4:20 pm (CET) for the French version.   var flash_video_player=get_video_player_path(); insert_player_for_external('Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-0753-kbps-640x360-25-fps-audio-64-kbps-44-kHz-stereo', 'mms://mediastream.cern.ch/MediaArchive/Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-Multirate-200-to-753-kbps-640x360-25-fps.wmv', 'false', 480, 360, 'https://mediastream.cern.ch/MediaArchive/Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-posterframe-640x360-at-10-percent.jpg', '1383406', true, 'Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-0600-kbps-maxH-360-25-fps-...

  3. Gamifying Video Object Segmentation.

    Science.gov (United States)

    Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

    2017-10-01

    Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

  4. Medical video server construction.

    Science.gov (United States)

    Dańda, Jacek; Juszkiewicz, Krzysztof; Leszczuk, Mikołaj; Loziak, Krzysztof; Papir, Zdzisław; Sikora, Marek; Watza, Rafal

    2003-01-01

    The paper discusses two implementation options for a Digital Video Library, a repository used for archiving, accessing, and browsing of video medical records. Two crucial issues to be decided on are a video compression format and a video streaming platform. The paper presents numerous decision factors that have to be taken into account. The compression formats being compared are DICOM as a format representative for medical applications, both MPEGs, and several new formats targeted for an IP networking. The comparison includes transmission rates supported, compression rates, and at least options for controlling a compression process. The second part of the paper presents the ISDN technique as a solution for provisioning of tele-consultation services between medical parties that are accessing resources uploaded to a digital video library. There are several backbone techniques (like corporate LANs/WANs, leased lines or even radio/satellite links) available, however, the availability of network resources for hospitals was the prevailing choice criterion pointing to ISDN solutions. Another way to provide access to the Digital Video Library is based on radio frequency domain solutions. The paper describes possibilities of both, wireless and cellular network's data transmission service to be used as a medical video server transport layer. For the cellular net-work based solution two communication techniques are used: Circuit Switched Data and Packet Switched Data.

  5. Vocabulary Constraint on Texts

    Directory of Open Access Journals (Sweden)

    C. Sutarsyah

    2008-01-01

    Full Text Available This case study was carried out in the English Education Department of State University of Malang. The aim of the study was to identify and describe the vocabulary in the reading text and to seek if the text is useful for reading skill development. A descriptive qualitative design was applied to obtain the data. For this purpose, some available computer programs were used to find the description of vocabulary in the texts. It was found that the 20 texts containing 7,945 words are dominated by low frequency words which account for 16.97% of the words in the texts. The high frequency words occurring in the texts were dominated by function words. In the case of word levels, it was found that the texts have very limited number of words from GSL (General Service List of English Words (West, 1953. The proportion of the first 1,000 words of GSL only accounts for 44.6%. The data also show that the texts contain too large proportion of words which are not in the three levels (the first 2,000 and UWL. These words account for 26.44% of the running words in the texts.  It is believed that the constraints are due to the selection of the texts which are made of a series of short-unrelated texts. This kind of text is subject to the accumulation of low frequency words especially those of content words and limited of words from GSL. It could also defeat the development of students' reading skills and vocabulary enrichment.

  6. Strategies to Increase Accuracy in Text Classification

    NARCIS (Netherlands)

    D. Blommesteijn (Dennis)

    2014-01-01

    htmlabstractText classification via supervised learning involves various steps from processing raw data, features extraction to training and validating classifiers. Within these steps implementation decisions are critical to the resulting classifier accuracy. This paper contains a report of the

  7. Text Mining for Protein Docking.

    Directory of Open Access Journals (Sweden)

    Varsha D Badal

    2015-12-01

    Full Text Available The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking. Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu. The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound

  8. Dictionaries for text production

    DEFF Research Database (Denmark)

    Fuertes-Olivera, Pedro; Bergenholtz, Henning

    2018-01-01

    Dictionaries for Text Production are information tools that are designed and constructed for helping users to produce (i.e. encode) texts, both oral and written texts. These can be broadly divided into two groups: (a) specialized text production dictionaries, i.e., dictionaries that only offer...... a small amount of lexicographic data, most or all of which are typically used in a production situation, e.g. synonym dictionaries, grammar and spelling dictionaries, collocation dictionaries, concept dictionaries such as the Longman Language Activator, which is advertised as the World’s First Production...... Dictionary; (b) general text production dictionaries, i.e., dictionaries that offer all or most of the lexicographic data that are typically used in a production situation. A review of existing production dictionaries reveals that there are many specialized text production dictionaries but only a few general...

  9. Dynamic Image Stitching for Panoramic Video

    Directory of Open Access Journals (Sweden)

    Jen-Yu Shieh

    2014-10-01

    Full Text Available The design of this paper is based on the Dynamic image titching for panoramic video. By utilizing OpenCV visual function data library and SIFT algorithm as the basis for presentation, this article brings forward Gaussian second differenced MoG which is processed basing on DoG Gaussian Difference Map to reduce order in synthesizing dynamic images and simplify the algorithm of the Gaussian pyramid structure. MSIFT matches with overlapping segmentation method to simplify the scope of feature extraction in order to enhance speed. And through this method traditional image synthesis can be improved without having to take lots of time in calculation and being limited by space and angle. This research uses four normal Webcams and two IPCAM coupled with several-wide angle lenses. By using wide-angle lenses to monitor over a wide range of an area and then by using image stitching panoramic effect is achieved. In terms of overall image application and control interface, Microsoft Visual Studio C# is adopted to a construct software interface. On a personal computer with 2.4-GHz CPU and 2-GB RAM and with the cameras fixed to it, the execution speed is three images per second, which reduces calculation time of the traditional algorithm.

  10. Queer video remix and LGBTQ online communities [multimedia

    Directory of Open Access Journals (Sweden)

    Elisa Kreisinger

    2012-03-01

    Full Text Available A curated selection of remix videos that edit pop culture texts and recut them into new works that explore themes of gender and sexual representation, or create new LGBTQ narratives from the original source material.

  11. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... About About the Veterans Crisis Line FAQs Veteran Suicide Spread the Word Videos Homeless Resources Additional Information ... About About the Veterans Crisis Line FAQs Veteran Suicide The Veterans Crisis Line text-messaging service does ...

  12. Video frame processor

    International Nuclear Information System (INIS)

    Joshi, V.M.; Agashe, Alok; Bairi, B.R.

    1993-01-01

    This report provides technical description regarding the Video Frame Processor (VFP) developed at Bhabha Atomic Research Centre. The instrument provides capture of video images available in CCIR format. Two memory planes each with a capacity of 512 x 512 x 8 bit data enable storage of two video image frames. The stored image can be processed on-line and on-line image subtraction can also be carried out for image comparisons. The VFP is a PC Add-on board and is I/O mapped within the host IBM PC/AT compatible computer. (author). 9 refs., 4 figs., 19 photographs

  13. High Dynamic Range Video

    CERN Document Server

    Myszkowski, Karol

    2008-01-01

    This book presents a complete pipeline forHDR image and video processing fromacquisition, through compression and quality evaluation, to display. At the HDR image and video acquisition stage specialized HDR sensors or multi-exposure techniques suitable for traditional cameras are discussed. Then, we present a practical solution for pixel values calibration in terms of photometric or radiometric quantities, which are required in some technically oriented applications. Also, we cover the problem of efficient image and video compression and encoding either for storage or transmission purposes, in

  14. 3D video

    CERN Document Server

    Lucas, Laurent; Loscos, Céline

    2013-01-01

    While 3D vision has existed for many years, the use of 3D cameras and video-based modeling by the film industry has induced an explosion of interest for 3D acquisition technology, 3D content and 3D displays. As such, 3D video has become one of the new technology trends of this century.The chapters in this book cover a large spectrum of areas connected to 3D video, which are presented both theoretically and technologically, while taking into account both physiological and perceptual aspects. Stepping away from traditional 3D vision, the authors, all currently involved in these areas, provide th

  15. Collaborative Video Sketching

    DEFF Research Database (Denmark)

    Henningsen, Birgitte; Gundersen, Peter Bukovica; Hautopp, Heidi

    2017-01-01

    This paper introduces to what we define as a collaborative video sketching process. This process links various sketching techniques with digital storytelling approaches and creative reflection processes in video productions. Traditionally, sketching has been used by designers across various...... findings: 1) They are based on a collaborative approach. 2) The sketches act as a mean to externalizing hypotheses and assumptions among the participants. Based on our analysis we present an overview of factors involved in collaborative video sketching and shows how the factors relate to steps, where...... the participants: shape, record, review and edit their work, leading the participants to new insights about their work....

  16. Categorizing Video Game Audio

    DEFF Research Database (Denmark)

    Westerberg, Andreas Rytter; Schoenau-Fog, Henrik

    2015-01-01

    they can use audio in video games. The conclusion of this study is that the current models' view of the diegetic spaces, used to categorize video game audio, is not t to categorize all sounds. This can however possibly be changed though a rethinking of how the player interprets audio.......This paper dives into the subject of video game audio and how it can be categorized in order to deliver a message to a player in the most precise way. A new categorization, with a new take on the diegetic spaces, can be used a tool of inspiration for sound- and game-designers to rethink how...

  17. PROTOTIPE VIDEO EDITOR DENGAN MENGGUNAKAN DIRECT X DAN DIRECT SHOW

    Directory of Open Access Journals (Sweden)

    Djoni Haryadi Setiabudi

    2004-01-01

    Full Text Available Technology development had given people the chance to capture their memorable moments in video format. A high quality digital video is a result of a good editing process. Which in turn, arise the new need of an editor application. In accordance to the problem, here the process of making a simple application for video editing needs. The application development use the programming techniques often applied in multimedia applications, especially video. First part of the application will begin with the video file compression and decompression, then we'll step into the editing part of the digital video file. Furthermore, the application also equipped with the facilities needed for the editing processes. The application made with Microsoft Visual C++ with DirectX technology, particularly DirectShow. The application provides basic facilities that will help the editing process of a digital video file. The application will produce an AVI format file after the editing process is finished. Through the testing process of this application shows the ability of this application to do the 'cut' and 'insert' of video files in AVI, MPEG, MPG and DAT formats. The 'cut' and 'insert' process only can be done in static order. Further, the aplication also provide the effects facility for transition process in each clip. Lastly, the process of saving the new edited video file in AVI format from the application. Abstract in Bahasa Indonesia : Perkembangan teknologi memberi kesempatan masyarakat untuk mengabadikan saat - saat yang penting menggunakan video. Pembentukan video digital yang baik membutuhkan proses editing yang baik pula. Untuk melakukan proses editing video digital dibutuhkan program editor. Berdasarkan permasalahan diatas maka pada penelitian ini dibuat prototipe editor sederhana untuk video digital. Pembuatan aplikasi memakai teknik pemrograman di bidang multimedia, khususnya video. Perencanaan dalam pembuatan aplikasi tersebut dimulai dengan pembentukan

  18. Instant Sublime Text starter

    CERN Document Server

    Haughee, Eric

    2013-01-01

    A starter which teaches the basic tasks to be performed with Sublime Text with the necessary practical examples and screenshots. This book requires only basic knowledge of the Internet and basic familiarity with any one of the three major operating systems, Windows, Linux, or Mac OS X. However, as Sublime Text 2 is primarily a text editor for writing software, many of the topics discussed will be specifically relevant to software development. That being said, the Sublime Text 2 Starter is also suitable for someone without a programming background who may be looking to learn one of the tools of

  19. Automatic association of chats and video tracks for activity learning and recognition in aerial video surveillance.

    Science.gov (United States)

    Hammoud, Riad I; Sahin, Cem S; Blasch, Erik P; Rhodes, Bradley J; Wang, Tao

    2014-10-22

    We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA) and multi-media indexing and explorer (MINER). VIVA utilizes analyst call-outs (ACOs) in the form of chat messages (voice-to-text) to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter. MINER includes: (1) a fusion of graphical track and text data using probabilistic methods; (2) an activity pattern learning framework to support querying an index of activities of interest (AOIs) and targets of interest (TOIs) by movement type and geolocation; and (3) a user interface to support streaming multi-intelligence data processing. We also present an activity pattern learning framework that uses the multi-source associated data as training to index a large archive of full-motion videos (FMV). VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection/false alarm results due to the complexity of the scenario. The novel use of ACOs and chat Sensors 2014, 14 19844 messages in video tracking paves the way for user interaction, correction and preparation of situation awareness reports.

  20. MPEG-7 based video annotation and browsing

    Science.gov (United States)

    Hoeynck, Michael; Auweiler, Thorsten; Wellhausen, Jens

    2003-11-01

    The huge amount of multimedia data produced worldwide requires annotation in order to enable universal content access and to provide content-based search-and-retrieval functionalities. Since manual video annotation can be time consuming, automatic annotation systems are required. We review recent approaches to content-based indexing and annotation of videos for different kind of sports and describe our approach to automatic annotation of equestrian sports videos. We especially concentrate on MPEG-7 based feature extraction and content description, where we apply different visual descriptors for cut detection. Further, we extract the temporal positions of single obstacles on the course by analyzing MPEG-7 edge information. Having determined single shot positions as well as the visual highlights, the information is jointly stored with meta-textual information in an MPEG-7 description scheme. Based on this information, we generate content summaries which can be utilized in a user-interface in order to provide content-based access to the video stream, but further for media browsing on a streaming server.

  1. Video sensor architecture for surveillance applications.

    Science.gov (United States)

    Sánchez, Jordi; Benet, Ginés; Simó, José E

    2012-01-01

    This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

  2. Common Virtual Path and Its Expedience for VBR Video Traffic

    Directory of Open Access Journals (Sweden)

    E. Chromy

    2008-04-01

    Full Text Available The paper deals with utilization of common Virtual Path (VP for variable bit rate (VBR video service. Video service is one of the main services for broadband networks. Research is oriented to statistical properties of common and separate VPs. Separate VP means that for each VBR traffic source one VP will be allocated. Common VP means that for multiple VBR sources one common VP is allocated. VBR video traffic source is modeled by discrete Markov chain.

  3. Subjective Video Quality Assessment in H.264/AVC Video Coding Standard

    Directory of Open Access Journals (Sweden)

    Z. Miličević

    2012-11-01

    Full Text Available This paper seeks to provide an approach for subjective video quality assessment in the H.264/AVC standard. For this purpose a special software program for the subjective assessment of quality of all the tested video sequences is developed. It was developed in accordance with recommendation ITU-T P.910, since it is suitable for the testing of multimedia applications. The obtained results show that in the proposed selective intra prediction and optimized inter prediction algorithm there is a small difference in picture quality (signal-to-noise ratio between decoded original and modified video sequences.

  4. Linguistics in Text Interpretation

    DEFF Research Database (Denmark)

    Togeby, Ole

    2011-01-01

    A model for how text interpretation proceeds from what is pronounced, through what is said to what is comunicated, and definition of the concepts 'presupposition' and 'implicature'.......A model for how text interpretation proceeds from what is pronounced, through what is said to what is comunicated, and definition of the concepts 'presupposition' and 'implicature'....

  5. LocText

    DEFF Research Database (Denmark)

    Cejuela, Juan Miguel; Vinchurkar, Shrikant; Goldberg, Tatyana

    2018-01-01

    trees and was trained and evaluated on a newly improved LocTextCorpus. Combined with an automatic named-entity recognizer, LocText achieved high precision (P = 86%±4). After completing development, we mined the latest research publications for three organisms: human (Homo sapiens), budding yeast...

  6. Systematic text condensation

    DEFF Research Database (Denmark)

    Malterud, Kirsti

    2012-01-01

    To present background, principles, and procedures for a strategy for qualitative analysis called systematic text condensation and discuss this approach compared with related strategies.......To present background, principles, and procedures for a strategy for qualitative analysis called systematic text condensation and discuss this approach compared with related strategies....

  7. The Perfect Text.

    Science.gov (United States)

    Russo, Ruth

    1998-01-01

    A chemistry teacher describes the elements of the ideal chemistry textbook. The perfect text is focused and helps students draw a coherent whole out of the myriad fragments of information and interpretation. The text would show chemistry as the central science necessary for understanding other sciences and would also root chemistry firmly in the…

  8. Text 2 Mind Map

    OpenAIRE

    Iona, John

    2017-01-01

    This is a review of the web resource 'Text 2 Mind Map' www.Text2MindMap.com. It covers what the resource is, and how it might be used in Library and education context, in particular for School Librarians.

  9. Text File Comparator

    Science.gov (United States)

    Kotler, R. S.

    1983-01-01

    File Comparator program IFCOMP, is text file comparator for IBM OS/VScompatable systems. IFCOMP accepts as input two text files and produces listing of differences in pseudo-update form. IFCOMP is very useful in monitoring changes made to software at the source code level.

  10. Heterogeneity image patch index and its application to consumer video summarization.

    Science.gov (United States)

    Dang, Chinh T; Radha, Hayder

    2014-06-01

    Automatic video summarization is indispensable for fast browsing and efficient management of large video libraries. In this paper, we introduce an image feature that we refer to as heterogeneity image patch (HIP) index. The proposed HIP index provides a new entropy-based measure of the heterogeneity of patches within any picture. By evaluating this index for every frame in a video sequence, we generate a HIP curve for that sequence. We exploit the HIP curve in solving two categories of video summarization applications: key frame extraction and dynamic video skimming. Under the key frame extraction frame-work, a set of candidate key frames is selected from abundant video frames based on the HIP curve. Then, a proposed patch-based image dissimilarity measure is used to create affinity matrix of these candidates. Finally, a set of key frames is extracted from the affinity matrix using a min–max based algorithm. Under video skimming, we propose a method to measure the distance between a video and its skimmed representation. The video skimming problem is then mapped into an optimization framework and solved by minimizing a HIP-based distance for a set of extracted excerpts. The HIP framework is pixel-based and does not require semantic information or complex camera motion estimation. Our simulation results are based on experiments performed on consumer videos and are compared with state-of-the-art methods. It is shown that the HIP approach outperforms other leading methods, while maintaining low complexity.

  11. PROBLEM PENDIDIKAN VIDEO GAMES DALAM PERSPEKTIF TEORI SIMULACRA JEAN BAUDRILLARD

    Directory of Open Access Journals (Sweden)

    Siti Murtiningsih, Joko Siswanto, M. Mukhtasar Syamsudin

    2013-05-01

    Full Text Available Abstract: Education Problems of Video Games in the Perspective of Jean Baudrillard’s Theory of Simulacra. In the era of digital age, we are witnessing how video games penetrate children’s daily life and it is believed to have some impacts on their cognitive and affective processes. Referring to hermeneutical approach, the present library research seeks to answer the question whether video games create a real identity or simply forge false consciousness in children. In the first step, the data were collected from bibliographi­cal sources that related to data. In the second step, the data were analyzed to examine the pedagogical-philosophical properties of the video games. The results indicate that video games change the way children view the world. Video games present the world as hiper-reality. Bu putting aside the negative values and maximizing the positive ones, the understanding of hiper-reality allows for the inculcation of children. Abstrak: Problem Pendidikan Video Games dalam Perspectif Teori Simulacra Jean Baudrillard. Permainan video games diyakini berdampak positif sekaligus negatif pada proses kognitif dan afektif anak.-anak. Terutama, video games berpengaruh pada proses internalisasi nilai-nilai dan pembentukan identitas mereka. Teknologi virtual yang disajikan oleh video games, seperti didekati oleh teori simulacra Jean Baudrillard, menyuguhkan jebakan akan realitas palsu. Melalui riset pustaka dengan metode "filsafat her­meneutis", dianalisis data untuk membangun refleksi filsafat pendidikan atas permainan video games itu. Hasil penelitian ini menyatakan video games menyuguhkan sebuah hiper-realitas dari simulasi realitas, atau simulacra dalam teori Jean Baudrillard. Simulacra adalah dunia yang terbentuk dari salinan realitas, yang menjadi acuan melebihi realitas asli. Disimpulkan bahwa video games menjadi semacam “ruang konseptual”, yang dibentuk oleh simulacra. Dengan mengenali hakikat hiper-realitas, video games dapat

  12. Adolescents and Video Games: Consumption of Leisure and the Social Construction of the Peer Group.

    Science.gov (United States)

    Panelas, Tom

    1983-01-01

    Addresses the role of video games in the lives of adolescents. Considers the significance of video games both as cultural "texts" and organized social activities. Examines motivations, practical interests, and behavior of suppliers and consumers of these products. (CMG)

  13. Photos and Videos

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Observers are required to take photos and/or videos of all incidentally caught sea turtles, marine mammals, seabirds and unusual or rare fish. On the first 3...

  14. Augmented video viewing: transforming video consumption into an active experience

    OpenAIRE

    WIJNANTS, Maarten; Leën, Jeroen; QUAX, Peter; LAMOTTE, Wim

    2014-01-01

    Traditional video productions fail to cater to the interactivity standards that the current generation of digitally native customers have become accustomed to. This paper therefore advertises the \\activation" of the video consumption process. In particular, it proposes to enhance HTML5 video playback with interactive features in order to transform video viewing into a dynamic pastime. The objective is to enable the authoring of more captivating and rewarding video experiences for end-users. T...

  15. Geographic Video 3d Data Model And Retrieval

    Science.gov (United States)

    Han, Z.; Cui, C.; Kong, Y.; Wu, H.

    2014-04-01

    Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

  16. Entropy-Based Video Steganalysis of Motion Vectors

    Directory of Open Access Journals (Sweden)

    Elaheh Sadat Sadat

    2018-04-01

    Full Text Available In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and the irregularity of each block increases the precision of the final video classification into cover and stego classes.

  17. A Review on Video-Based Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Shian-Ru Ke

    2013-06-01

    Full Text Available This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems.

  18. Automatic Emotional State Detection using Facial Expression Dynamic in Videos

    Directory of Open Access Journals (Sweden)

    Hongying Meng

    2014-11-01

    Full Text Available In this paper, an automatic emotion detection system is built for a computer or machine to detect the emotional state from facial expressions in human computer communication. Firstly, dynamic motion features are extracted from facial expression videos and then advanced machine learning methods for classification and regression are used to predict the emotional states. The system is evaluated on two publicly available datasets, i.e. GEMEP_FERA and AVEC2013, and satisfied performances are achieved in comparison with the baseline results provided. With this emotional state detection capability, a machine can read the facial expression of its user automatically. This technique can be integrated into applications such as smart robots, interactive games and smart surveillance systems.

  19. Multi-view video segmentation and tracking for video surveillance

    Science.gov (United States)

    Mohammadi, Gelareh; Dufaux, Frederic; Minh, Thien Ha; Ebrahimi, Touradj

    2009-05-01

    Tracking moving objects is a critical step for smart video surveillance systems. Despite the complexity increase, multiple camera systems exhibit the undoubted advantages of covering wide areas and handling the occurrence of occlusions by exploiting the different viewpoints. The technical problems in multiple camera systems are several: installation, calibration, objects matching, switching, data fusion, and occlusion handling. In this paper, we address the issue of tracking moving objects in an environment covered by multiple un-calibrated cameras with overlapping fields of view, typical of most surveillance setups. Our main objective is to create a framework that can be used to integrate objecttracking information from multiple video sources. Basically, the proposed technique consists of the following steps. We first perform a single-view tracking algorithm on each camera view, and then apply a consistent object labeling algorithm on all views. In the next step, we verify objects in each view separately for inconsistencies. Correspondent objects are extracted through a Homography transform from one view to the other and vice versa. Having found the correspondent objects of different views, we partition each object into homogeneous regions. In the last step, we apply the Homography transform to find the region map of first view in the second view and vice versa. For each region (in the main frame and mapped frame) a set of descriptors are extracted to find the best match between two views based on region descriptors similarity. This method is able to deal with multiple objects. Track management issues such as occlusion, appearance and disappearance of objects are resolved using information from all views. This method is capable of tracking rigid and deformable objects and this versatility lets it to be suitable for different application scenarios.

  20. Zum Bildungspotenzial biblischer Texte

    Directory of Open Access Journals (Sweden)

    Theis, Joachim

    2017-11-01

    Full Text Available Biblical education as a holistic process goes far beyond biblical learning. It must be understood as a lifelong process, in which both biblical texts and their understanders operate appropriating their counterpart in a dialogical way. – Neither does the recipient’s horizon of understanding appear as an empty room, which had to be filled with the text only, nor is the latter a dead material one could only examine cognitively. The recipient discovers the meaning of the biblical text recomposing it by existential appropriation. So the text is brought to live in each individual reality. Both scientific insights and subjective structures as well as the understanders’ community must be included to avoid potential one-sidednesses. Unfortunately, a special negative association obscures the approach of the bible very often: Still biblical work as part of religious education appears in a cognitively oriented habit, which is neither regarding the vitality and sovereignty of the biblical texts nor the students’ desire for meaning. Moreover, the bible is getting misused for teaching moral terms or pontifications. Such downfalls can be disrupted by biblical didactics which are empowerment didactics. Regarding the sovereignty of biblical texts, these didactics assist the understander with his/her individuation by opening the texts with focus on the understander’s otherness. Thus each the text and the recipient become subjects in a dialogue. The approach of the Biblical-Enabling-Didactics leads the Bible to become always new a book of life. Understanding them from within their hermeneutics, empowerment didactics could be raised to the principle of biblical didactics in general and grow into an essential element of holistic education.

  1. Industrial-Strength Streaming Video.

    Science.gov (United States)

    Avgerakis, George; Waring, Becky

    1997-01-01

    Corporate training, financial services, entertainment, and education are among the top applications for streaming video servers, which send video to the desktop without downloading the whole file to the hard disk, saving time and eliminating copyrights questions. Examines streaming video technology, lists ten tips for better net video, and ranks…

  2. A Framework for Video Modeling

    NARCIS (Netherlands)

    Petkovic, M.; Jonker, Willem

    In recent years, research in video databases has increased greatly, but relatively little work has been done in the area of semantic content-based retrieval. In this paper, we present a framework for video modelling with emphasis on semantic content of video data. The video data model presented

  3. Hybrid Video Stabilization for Mobile Vehicle Detection on SURF in Aerial Surveillance

    Directory of Open Access Journals (Sweden)

    Gao Chunxian

    2015-01-01

    Full Text Available Detection of moving vehicles in aerial video sequences is of great importance with many promising applications in surveillance, intelligence transportation, or public service applications such as emergency evacuation and policy security. However, vehicle detection is a challenging task due to global camera motion, low resolution of vehicles, and low contrast between vehicles and background. In this paper, we present a hybrid method to efficiently detect moving vehicle in aerial videos. Firstly, local feature extraction and matching were performed to estimate the global motion. It was demonstrated that the Speeded Up Robust Feature (SURF key points were more suitable for the stabilization task. Then, a list of dynamic pixels was obtained and grouped for different moving vehicles by comparing the different optical flow normal. To enhance the precision of detection, some preprocessing methods were applied to the surveillance system, such as road extraction and other features. A quantitative evaluation on real video sequences indicated that the proposed method improved the detection performance significantly.

  4. A video-based approach to calibrating car-following parameters in VISSIM for urban traffic

    Directory of Open Access Journals (Sweden)

    Zhengyang Lu

    2016-08-01

    Full Text Available Microscopic simulation models need to be calibrated to represent realistic local traffic conditions. Traditional calibration methods are conducted by searching for the model parameter set that minimizes the discrepancies of certain macroscopic metrics between simulation results and field observations. However, this process could easily lead to inappropriate selection of calibration parameters and thus erroneous simulation results. This paper proposes a video-based approach to incorporate direct measurements of car-following parameters into the process of VISSIM model calibration. The proposed method applies automated video processing techniques to extract vehicle trajectory data and utilizes the trajectory data to determine values of certain car-following parameters in VISSIM. This paper first describes the calibration procedure step by step, and then applies the method to a case study of simulating traffic at a signalized intersection in VISSIM. From the field-collected video footage, trajectories of 1229 through-movement vehicles were extracted and analyzed to calibrate three car-following parameters regarding desired speed, desired acceleration, and safe following distance, respectively. The case study demonstrates the advantages and feasibility of the proposed approach.

  5. Key Frame Extraction in the Summary Space.

    Science.gov (United States)

    Li, Xuelong; Zhao, Bin; Lu, Xiaoqiang; Xuelong Li; Bin Zhao; Xiaoqiang Lu; Lu, Xiaoqiang; Li, Xuelong; Zhao, Bin

    2018-06-01

    Key frame extraction is an efficient way to create the video summary which helps users obtain a quick comprehension of the video content. Generally, the key frames should be representative of the video content, meanwhile, diverse to reduce the redundancy. Based on the assumption that the video data are near a subspace of a high-dimensional space, a new approach, named as key frame extraction in the summary space, is proposed for key frame extraction in this paper. The proposed approach aims to find the representative frames of the video and filter out similar frames from the representative frame set. First of all, the video data are mapped to a high-dimensional space, named as summary space. Then, a new representation is learned for each frame by analyzing the intrinsic structure of the summary space. Specifically, the learned representation can reflect the representativeness of the frame, and is utilized to select representative frames. Next, the perceptual hash algorithm is employed to measure the similarity of representative frames. As a result, the key frame set is obtained after filtering out similar frames from the representative frame set. Finally, the video summary is constructed by assigning the key frames in temporal order. Additionally, the ground truth, created by filtering out similar frames from human-created summaries, is utilized to evaluate the quality of the video summary. Compared with several traditional approaches, the experimental results on 80 videos from two datasets indicate the superior performance of our approach.

  6. Automated music selection of video ads

    Directory of Open Access Journals (Sweden)

    Wiesener Oliver

    2017-07-01

    Full Text Available The importance of video ads on social media platforms can be measured by views. For instance, Samsung’s commercial ad for one of its new smartphones reached more than 46 million viewers at Youtube. A video ad addresses the visual as well as the auditive sense of users. Often the visual sense is busy in the sense that users focus other screens than the screen with the video ad. This is called the second screen syndrome. Therefore, the importance of the audio channel seems to grow. To get back the visual attention of users that are deflected from other visual impulses it appears reasonable to adapt the music to the target group. Additionally, it appears useful to adapt the music to content of the video. Thus, the overall success of a video ad could by increased by increasing the attention of the users. Humans typically make the decision about the music of a video ad. If there is a correlation between music, products and target groups, a digitization of the music selection process seems to be possible. Since the digitization progress in the music sector is mainly focused on music composing this article strives for making a first step towards the digitization of the music selection.

  7. A Method for Estimating Surveillance Video Georeferences

    Directory of Open Access Journals (Sweden)

    Aleksandar Milosavljević

    2017-07-01

    Full Text Available The integration of a surveillance camera video with a three-dimensional (3D geographic information system (GIS requires the georeferencing of that video. Since a video consists of separate frames, each frame must be georeferenced. To georeference a video frame, we rely on the information about the camera view at the moment that the frame was captured. A camera view in 3D space is completely determined by the camera position, orientation, and field-of-view. Since the accurate measuring of these parameters can be extremely difficult, in this paper we propose a method for their estimation based on matching video frame coordinates of certain point features with their 3D geographic locations. To obtain these coordinates, we rely on high-resolution orthophotos and digital elevation models (DEM of the area of interest. Once an adequate number of points are matched, Levenberg–Marquardt iterative optimization is applied to find the most suitable video frame georeference, i.e., position and orientation of the camera.

  8. 360-degree videos: a new visualization technique for astrophysical simulations

    Science.gov (United States)

    Russell, Christopher M. P.

    2017-11-01

    360-degree videos are a new type of movie that renders over all 4π steradian. Video sharing sites such as YouTube now allow this unique content to be shared via virtual reality (VR) goggles, hand-held smartphones/tablets, and computers. Creating 360° videos from astrophysical simulations is not only a new way to view these simulations as you are immersed in them, but is also a way to create engaging content for outreach to the public. We present what we believe is the first 360° video of an astrophysical simulation: a hydrodynamics calculation of the central parsec of the Galactic centre. We also describe how to create such movies, and briefly comment on what new science can be extracted from astrophysical simulations using 360° videos.

  9. Practicality in Virtuality: Finding Student Meaning in Video Game Education

    Science.gov (United States)

    Barko, Timothy; Sadler, Troy D.

    2013-04-01

    This paper looks at the conceptual differences between video game learning and traditional classroom and laboratory learning. It explores the notion of virtual experience by comparing a commonly used high school laboratory protocol on DNA extraction with a similar experience provided by a biotechnology themed video game. When considered conceptually, the notion of virtual experience is not limited to those experiences generated by computer aided technology, as with a video game or computer simulation. The notion of virtuality can apply to many real world experiences as well. It is proposed that the medium of the learning experience, be it video game or classroom, is not an important distinction to consider; instead, we should seek to determine what kinds of meaningful experiences apply for both classrooms and video games.

  10. No-Reference Video Quality Assessment by HEVC Codec Analysis

    DEFF Research Database (Denmark)

    Huang, Xin; Søgaard, Jacob; Forchhammer, Søren

    2015-01-01

    This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by High Efficiency Video Coding (HEVC). The proposed assessment can be performed either as a BitstreamBased (BB) method or as a Pixel-Based (PB). It extracts or estimates...... the transform coefficients, estimates the distortion, and assesses the video quality. The proposed scheme generates VQA features based on Intra coded frames, and then maps features using an Elastic Net to predict subjective video quality. A set of HEVC coded 4K UHD sequences are tested. Results show...... that the quality scores computed by the proposed method are highly correlated with the subjective assessment....

  11. Video segmentation and camera motion characterization using compressed data

    Science.gov (United States)

    Milanese, Ruggero; Deguillaume, Frederic; Jacot-Descombes, Alain

    1997-10-01

    We address the problem of automatically extracting visual indexes from videos, in order to provide sophisticated access methods to the contents of a video server. We focus on tow tasks, namely the decomposition of a video clip into uniform segments, and the characterization of each shot by camera motion parameters. For the first task we use a Bayesian classification approach to detecting scene cuts by analyzing motion vectors. For the second task a least- squares fitting procedure determines the pan/tilt/zoom camera parameters. In order to guarantee the highest processing speed, all techniques process and analyze directly MPEG-1 motion vectors, without need for video decompression. Experimental results are reported for a database of news video clips.

  12. Understanding Infrastructure Resiliency in Chennai, India Using Twitter’s Geotags and Texts: A Preliminary Study

    Directory of Open Access Journals (Sweden)

    Wai K. Chong

    2018-04-01

    Full Text Available Geotagging is the process of labeling data and information with geographical identification metadata, and text mining refers to the process of deriving information from text through data analytics. Geotagging and text mining are used to mine rich sources of social media data, such as video, website, text, and Quick Response (QR code. They have been frequently used to model consumer behaviors and market trends. This study uses both techniques to understand the resilience of infrastructure in Chennai, India using data mined from the 2015 flood. This paper presents a conceptual study on the potential use of social media (Twitter in this case to better understand infrastructure resiliency. Using feature-extraction techniques, the research team extracted Twitter data from tweets generated by the Chennai population during the flood. First, this study shows that these techniques are useful in identifying locations, defects, and failure intensities of infrastructure using the location metadata from geotags, words containing the locations, and the frequencies of tweets from each location. However, more efforts are needed to better utilize the texts generated from the tweets, including a better understanding of the cultural contexts of the words used in the tweets, the contexts of the words used to describe the incidents, and the least frequently used words. Keywords: Social media, Flooding, Engineering design

  13. Robust Adaptable Video Copy Detection

    DEFF Research Database (Denmark)

    Assent, Ira; Kremer, Hardy

    2009-01-01

    in contrast). Our query processing combines filtering and indexing structures for efficient multistep computation of video copies under this model. We show that our model successfully identifies altered video copies and does so more reliably than existing models.......Video copy detection should be capable of identifying video copies subject to alterations e.g. in video contrast or frame rates. We propose a video copy detection scheme that allows for adaptable detection of videos that are altered temporally (e.g. frame rate change) and/or visually (e.g. change...

  14. EST: Evading Scientific Text.

    Science.gov (United States)

    Ward, Jeremy

    2001-01-01

    Examines chemical engineering students' attitudes to text and other parts of English language textbooks. A questionnaire was administered to a group of undergraduates. Results reveal one way students get around the problem of textbook reading. (Author/VWL)

  15. nal Sesotho texts

    African Journals Online (AJOL)

    with literary texts written in indigenous South African languages. The project ... Homi Bhabha uses the words of Salman Rushdie to underline the fact that new .... I could not conceptualise an African-language-to-African-language dictionary. An.

  16. Plagiarism in Academic Texts

    Directory of Open Access Journals (Sweden)

    Marta Eugenia Rojas-Porras

    2012-08-01

    Full Text Available The ethical and social responsibility of citing the sources in a scientific or artistic work is undeniable. This paper explores, in a preliminary way, academic plagiarism in its various forms. It includes findings based on a forensic analysis. The purpose of this paper is to raise awareness on the importance of considering these details when writing and publishing a text. Hopefully, this analysis may put the issue under discussion.

  17. Machine Translation from Text

    Science.gov (United States)

    Habash, Nizar; Olive, Joseph; Christianson, Caitlin; McCary, John

    Machine translation (MT) from text, the topic of this chapter, is perhaps the heart of the GALE project. Beyond being a well defined application that stands on its own, MT from text is the link between the automatic speech recognition component and the distillation component. The focus of MT in GALE is on translating from Arabic or Chinese to English. The three languages represent a wide range of linguistic diversity and make the GALE MT task rather challenging and exciting.

  18. A Proposed Arabic Handwritten Text Normalization Method

    Directory of Open Access Journals (Sweden)

    Tarik Abu-Ain

    2014-11-01

    Full Text Available Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and characters recognition. In the present article, a new method for text baseline detection, straightening, and slant correction for Arabic handwritten texts is proposed. The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direction features of the skeletons are extracted, and the candidate baseline regions are determined. After that, selection of the correct baseline region is done, and finally, the baselines of all components are aligned with the writing line.  The experiments are conducted on IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.

  19. A systematic review of methods for studying consumer health YouTube videos, with implications for systematic reviews

    Directory of Open Access Journals (Sweden)

    Margaret Sampson

    2013-09-01

    Full Text Available Background. YouTube is an increasingly important medium for consumer health information – with content provided by healthcare professionals, government and non-government organizations, industry, and consumers themselves. It is a rapidly developing area of study for healthcare researchers. We examine the methods used in reviews of YouTube consumer health videos to identify trends and best practices.Methods and Materials. Published reviews of consumer-oriented health-related YouTube videos were identified through PubMed. Data extracted from these studies included type of journal, topic, characteristics of the search, methods of review including number of reviewers and method to achieve consensus between reviewers, inclusion and exclusion criteria, characteristics of the videos reported, ethical oversight, and follow-up.Results. Thirty-three studies were identified. Most were recent and published in specialty journals. Typically, these included more than 100 videos, and were examined by multiple reviewers. Most studies described characteristics of the videos, number of views, and sometime characteristics of the viewers. Accuracy of portrayal of the health issue under consideration was a common focus.Conclusion. Optimal transparency and reproducibility of studies of YouTube health-related videos can be achieved by following guidance designed for systematic review reporting, with attention to several elements specific to the video medium. Particularly when seeking to replicate consumer viewing behavior, investigators should consider the method used to select search terms, and use a snowballing rather than a sequential screening approach. Discontinuation protocols for online screening of relevance ranked search results is an area identified for further development.

  20. SHIP CLASSIFICATION FROM MULTISPECTRAL VIDEOS

    Directory of Open Access Journals (Sweden)

    Frederique Robert-Inacio

    2012-05-01

    Full Text Available Surveillance of a seaport can be achieved by different means: radar, sonar, cameras, radio communications and so on. Such a surveillance aims, on the one hand, to manage cargo and tanker traffic, and, on the other hand, to prevent terrorist attacks in sensitive areas. In this paper an application to video-surveillance of a seaport entrance is presented, and more particularly, the different steps enabling to classify mobile shapes. This classification is based on a parameter measuring the similarity degree between the shape under study and a set of reference shapes. The classification result describes the considered mobile in terms of shape and speed.

  1. Stemming Malay Text and Its Application in Automatic Text Categorization

    Science.gov (United States)

    Yasukawa, Michiko; Lim, Hui Tian; Yokoo, Hidetoshi

    In Malay language, there are no conjugations and declensions and affixes have important grammatical functions. In Malay, the same word may function as a noun, an adjective, an adverb, or, a verb, depending on its position in the sentence. Although extensively simple root words are used in informal conversations, it is essential to use the precise words in formal speech or written texts. In Malay, to make sentences clear, derivative words are used. Derivation is achieved mainly by the use of affixes. There are approximately a hundred possible derivative forms of a root word in written language of the educated Malay. Therefore, the composition of Malay words may be complicated. Although there are several types of stemming algorithms available for text processing in English and some other languages, they cannot be used to overcome the difficulties in Malay word stemming. Stemming is the process of reducing various words to their root forms in order to improve the effectiveness of text processing in information systems. It is essential to avoid both over-stemming and under-stemming errors. We have developed a new Malay stemmer (stemming algorithm) for removing inflectional and derivational affixes. Our stemmer uses a set of affix rules and two types of dictionaries: a root-word dictionary and a derivative-word dictionary. The use of set of rules is aimed at reducing the occurrence of under-stemming errors, while that of the dictionaries is believed to reduce the occurrence of over-stemming errors. We performed an experiment to evaluate the application of our stemmer in text mining software. For the experiment, text data used were actual web pages collected from the World Wide Web to demonstrate the effectiveness of our Malay stemming algorithm. The experimental results showed that our stemmer can effectively increase the precision of the extracted Boolean expressions for text categorization.

  2. Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients

    Directory of Open Access Journals (Sweden)

    Jing Li

    2014-01-01

    Full Text Available Based on video recordings of the movement of the patients with epilepsy, this paper proposed a human action recognition scheme to detect distinct motion patterns and to distinguish the normal status from the abnormal status of epileptic patients. The scheme first extracts local features and holistic features, which are complementary to each other. Afterwards, a support vector machine is applied to classification. Based on the experimental results, this scheme obtains a satisfactory classification result and provides a fundamental analysis towards the human-robot interaction with socially assistive robots in caring the patients with epilepsy (or other patients with brain disorders in order to protect them from injury.

  3. Measuring energy expenditure in sports by thermal video analysis

    DEFF Research Database (Denmark)

    Gade, Rikke; Larsen, Ryan Godsk; Moeslund, Thomas B.

    2017-01-01

    Estimation of human energy expenditure in sports and exercise contributes to performance analyses and tracking of physical activity levels. The focus of this work is to develop a video-based method for estimation of energy expenditure in athletes. We propose a method using thermal video analysis...... to automatically extract the cyclic motion pattern, in walking and running represented as steps, and analyse the frequency. Experiments are performed with one subject in two different tests, each at 5, 8, 10, and 12 km/h. The results of our proposed video-based method is compared to concurrent measurements...

  4. Research of Video Steganalysis Algorithm Based on H265 Protocol

    Directory of Open Access Journals (Sweden)

    Wu Kaicheng

    2015-01-01

    This paper researches LSB matching VSA based on H265 protocol with the research background of 26 original Video sequences, it firstly extracts classification features out from training samples as input of SVM, and trains in SVM to obtain high-quality category classification model, and then tests whether there is suspicious information in the video sample. The experimental results show that VSA algorithm based on LSB matching can be more practical to obtain all frame embedded secret information and carrier and video of local frame embedded. In addition, VSA adopts the method of frame by frame with a strong robustness in resisting attack in the corresponding time domain.

  5. Teasing Apart Complex Motions using VideoPoint

    Science.gov (United States)

    Fischer, Mark

    2002-10-01

    Using video analysis software such as VideoPoint, it is possible to explore the physics of any phenomenon that can be captured on videotape. The good news is that complex motions can be filmed and analyzed. The bad news is that the motions can become very complex very quickly. An example of such a complicated motion, the 2-dimensional motion of an object as filmed by a camera that is moving and rotating in the same plane will be discussed. Methods for extracting the desired object motion will be given as well as suggestions for shooting more easily analyzable video clips.

  6. Methods and Algorithms for Detecting Objects in Video Files

    Directory of Open Access Journals (Sweden)

    Nguyen The Cuong

    2018-01-01

    Full Text Available Video files are files that store motion pictures and sounds like in real life. In today's world, the need for automated processing of information in video files is increasing. Automated processing of information has a wide range of application including office/home surveillance cameras, traffic control, sports applications, remote object detection, and others. In particular, detection and tracking of object movement in video file plays an important role. This article describes the methods of detecting objects in video files. Today, this problem in the field of computer vision is being studied worldwide.

  7. An Adaptive Motion Segmentation for Automated Video Surveillance

    Directory of Open Access Journals (Sweden)

    Hossain MJulius

    2008-01-01

    Full Text Available This paper presents an adaptive motion segmentation algorithm utilizing spatiotemporal information of three most recent frames. The algorithm initially extracts the moving edges applying a novel flexible edge matching technique which makes use of a combined distance transformation image. Then watershed-based iterative algorithm is employed to segment the moving object region from the extracted moving edges. The challenges of existing three-frame-based methods include slow movement, edge localization error, minor movement of camera, and homogeneity of background and foreground region. The proposed method represents edges as segments and uses a flexible edge matching algorithm to deal with edge localization error and minor movement of camera. The combined distance transformation image works in favor of accumulating gradient information of overlapping region which effectively improves the sensitivity to slow movement. The segmentation algorithm uses watershed, gradient information of difference image, and extracted moving edges. It helps to segment moving object region with more accurate boundary even some part of the moving edges cannot be detected due to region homogeneity or other reasons during the detection step. Experimental results using different types of video sequences are presented to demonstrate the efficiency and accuracy of the proposed method.

  8. Medical students' perceptions of video-linked lectures and video-streaming

    Directory of Open Access Journals (Sweden)

    Karen Mattick

    2010-12-01

    Full Text Available Video-linked lectures allow healthcare students across multiple sites, and between university and hospital bases, to come together for the purposes of shared teaching. Recording and streaming video-linked lectures allows students to view them at a later date and provides an additional resource to support student learning. As part of a UK Higher Education Academy-funded Pathfinder project, this study explored medical students' perceptions of video-linked lectures and video-streaming, and their impact on learning. The methodology involved semi-structured interviews with 20 undergraduate medical students across four sites and five year groups. Several key themes emerged from the analysis. Students generally preferred live lectures at the home site and saw interaction between sites as a major challenge. Students reported that their attendance at live lectures was not affected by the availability of streamed lectures and tended to be influenced more by the topic and speaker than the technical arrangements. These findings will inform other educators interested in employing similar video technologies in their teaching.Keywords: video-linked lecture; video-streaming; student perceptions; decisionmaking; cross-campus teaching.

  9. TEXT Energy Storage System

    International Nuclear Information System (INIS)

    Weldon, W.F.; Rylander, H.G.; Woodson, H.H.

    1977-01-01

    The Texas Experimental Tokamak (TEXT) Enery Storage System, designed by the Center for Electromechanics (CEM), consists of four 50 MJ, 125 V homopolar generators and their auxiliaries and is designed to power the toroidal and poloidal field coils of TEXT on a two-minute duty cycle. The four 50 MJ generators connected in series were chosen because they represent the minimum cost configuration and also represent a minimal scale up from the successful 5.0 MJ homopolar generator designed, built, and operated by the CEM

  10. Video Multiple Watermarking Technique Based on Image Interlacing Using DWT

    Directory of Open Access Journals (Sweden)

    Mohamed M. Ibrahim

    2014-01-01

    Full Text Available Digital watermarking is one of the important techniques to secure digital media files in the domains of data authentication and copyright protection. In the nonblind watermarking systems, the need of the original host file in the watermark recovery operation makes an overhead over the system resources, doubles memory capacity, and doubles communications bandwidth. In this paper, a robust video multiple watermarking technique is proposed to solve this problem. This technique is based on image interlacing. In this technique, three-level discrete wavelet transform (DWT is used as a watermark embedding/extracting domain, Arnold transform is used as a watermark encryption/decryption method, and different types of media (gray image, color image, and video are used as watermarks. The robustness of this technique is tested by applying different types of attacks such as: geometric, noising, format-compression, and image-processing attacks. The simulation results show the effectiveness and good performance of the proposed technique in saving system resources, memory capacity, and communications bandwidth.

  11. Video Synchronization With Bit-Rate Signals and Correntropy Function

    Directory of Open Access Journals (Sweden)

    Igor Pereira

    2017-09-01

    Full Text Available We propose an approach for the synchronization of video streams using correntropy. Essentially, the time offset is calculated on the basis of the instantaneous transfer rates of the video streams that are extracted in the form of a univariate signal known as variable bit-rate (VBR. The state-of-the-art approach uses a window segmentation strategy that is based on consensual zero-mean normalized cross-correlation (ZNCC. This strategy has an elevated computational complexity, making its application to synchronizing online data streaming difficult. Hence, our proposal uses a different window strategy that, together with the correntropy function, allows the synchronization to be performed for online applications. This provides equivalent synchronization scores with a rapid offset determination as the streams come into the system. The efficiency of our approach has been verified through experiments that demonstrate its viability with values that are as precise as those obtained by ZNCC. The proposed approach scored 81 % in time reference classification against the equivalent 81 % of the state-of-the-art approach, requiring much less computational power.

  12. Perceived Quality of Full HD Video - Subjective Quality Assessment

    Directory of Open Access Journals (Sweden)

    Juraj Bienik

    2016-01-01

    Full Text Available In recent years, an interest in multimedia services has become a global trend and this trend is still rising. The video quality is a very significant part from the bundle of multimedia services, which leads to a requirement for quality assessment in the video domain. Video quality of a streamed video across IP networks is generally influenced by two factors “transmission link imperfection and efficiency of compression standards. This paper deals with subjective video quality assessment and the impact of the compression standards H.264, H.265 and VP9 on perceived video quality of these compression standards. The evaluation is done for four full HD sequences, the difference of scenes is in the content“ distinction is based on Spatial (SI and Temporal (TI Index of test sequences. Finally, experimental results follow up to 30% bitrate reducing of H.265 and VP9 compared with the reference H.264.

  13. Video over DSL with LDGM Codes for Interactive Applications

    Directory of Open Access Journals (Sweden)

    Laith Al-Jobouri

    2016-05-01

    Full Text Available Digital Subscriber Line (DSL network access is subject to error bursts, which, for interactive video, can introduce unacceptable latencies if video packets need to be re-sent. If the video packets are protected against errors with Forward Error Correction (FEC, calculation of the application-layer channel codes themselves may also introduce additional latency. This paper proposes Low-Density Generator Matrix (LDGM codes rather than other popular codes because they are more suitable for interactive video streaming, not only for their computational simplicity but also for their licensing advantage. The paper demonstrates that a reduction of up to 4 dB in video distortion is achievable with LDGM Application Layer (AL FEC. In addition, an extension to the LDGM scheme is demonstrated, which works by rearranging the columns of the parity check matrix so as to make it even more resilient to burst errors. Telemedicine and video conferencing are typical target applications.

  14. Effective Quality-of-Service Renegotiating Schemes for Streaming Video

    Directory of Open Access Journals (Sweden)

    Song Hwangjun

    2004-01-01

    Full Text Available This paper presents effective quality-of-service renegotiating schemes for streaming video. The conventional network supporting quality of service generally allows a negotiation at a call setup. However, it is not efficient for the video application since the compressed video traffic is statistically nonstationary. Thus, we consider the network supporting quality-of-service renegotiations during the data transmission and study effective quality-of-service renegotiating schemes for streaming video. The token bucket model, whose parameters are token filling rate and token bucket size, is adopted for the video traffic model. The renegotiating time instants and the parameters are determined by analyzing the statistical information of compressed video traffic. In this paper, two renegotiating approaches, that is, fixed renegotiating interval case and variable renegotiating interval case, are examined. Finally, the experimental results are provided to show the performance of the proposed schemes.

  15. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available Veterans Crisis Line Skip to Main Content SuicidePreventionLifeline.org Get Help Materials Get Involved Crisis Centers About Be There ... see more videos from Veterans Health Administration Veterans Crisis Line -- After the Call see more videos from ...

  16. New mathematical cuneiform texts

    CERN Document Server

    Friberg, Jöran

    2016-01-01

    This monograph presents in great detail a large number of both unpublished and previously published Babylonian mathematical texts in the cuneiform script. It is a continuation of the work A Remarkable Collection of Babylonian Mathematical Texts (Springer 2007) written by Jöran Friberg, the leading expert on Babylonian mathematics. Focussing on the big picture, Friberg explores in this book several Late Babylonian arithmetical and metro-mathematical table texts from the sites of Babylon, Uruk and Sippar, collections of mathematical exercises from four Old Babylonian sites, as well as a new text from Early Dynastic/Early Sargonic Umma, which is the oldest known collection of mathematical exercises. A table of reciprocals from the end of the third millennium BC, differing radically from well-documented but younger tables of reciprocals from the Neo-Sumerian and Old-Babylonian periods, as well as a fragment of a Neo-Sumerian clay tablet showing a new type of a labyrinth are also discussed. The material is presen...

  17. The Emar Lexical Texts

    NARCIS (Netherlands)

    Gantzert, Merijn

    2011-01-01

    This four-part work provides a philological analysis and a theoretical interpretation of the cuneiform lexical texts found in the Late Bronze Age city of Emar, in present-day Syria. These word and sign lists, commonly dated to around 1100 BC, were almost all found in the archive of a single school.

  18. Text Induced Spelling Correction

    NARCIS (Netherlands)

    Reynaert, M.W.C.

    2004-01-01

    We present TISC, a language-independent and context-sensitive spelling checking and correction system designed to facilitate the automatic removal of non-word spelling errors in large corpora. Its lexicon is derived from a very large corpus of raw text, without supervision, and contains word

  19. Texts and Readers.

    Science.gov (United States)

    Iser, Wolfgang

    1980-01-01

    Notes that, since fictional discourse need not reflect prevailing systems of meaning and norms or values, readers gain detachment from their own presuppositions; by constituting and formulating text-sense, readers are constituting and formulating their own cognition and becoming aware of the operations for doing so. (FL)

  20. Documents and legal texts

    International Nuclear Information System (INIS)

    2017-01-01

    This section treats of the following documents and legal texts: 1 - Belgium 29 June 2014 - Act amending the Act of 22 July 1985 on Third-Party Liability in the Field of Nuclear Energy; 2 - Belgium, 7 December 2016. - Act amending the Act of 22 July 1985 on Third-Party Liability in the Field of Nuclear Energy