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  1. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
  2. 2003 Conference on Computer Vision and Pattern Recognition Workshop
  3. Volume 4 - 2003
  4. A Video Event Detection and Mining Framework
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2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
CVPR 2011 WORKSHOPS
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops
2004 Conference on Computer Vision and Pattern Recognition Workshop
2003 Conference on Computer Vision and Pattern Recognition Workshop
Volume 9 - 2003
Volume 8 - 2003
Volume 7 - 2003
Volume 6 - 2003
Volume 5 - 2003
Volume 4 - 2003
Time-dependent HMMs for visual intrusion detection
Estimating Tracking Sources and Sinks
Generic Event Detection in Sports Video using Cinematic Features
Principal Video Shot: Linking Low-Level Perceptional Features to Semantic Video Events
ARGMode - Activity Recognition using Graphical Models
Hierarchical Language-based Representation of Events in Video Streams
P-Net: A Representation for Partially-Sequenced, Multi-stream Activity
A Factorization Approach for Activity Recognition
A Video Event Detection and Mining Framework
Volume 3 - 2003
Volume 2 - 2003
Volume 1 - 2003
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition

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A Video Event Detection and Mining Framework

Content Provider IEEE Xplore Digital Library
Author Guler, Sadiye Liang, Winnie H. Pushee, Ian A.
Copyright Year 2003
Description Author affiliation: Northrop Grumman Information Technology / TASC (Guler, Sadiye; Liang, Winnie H.; Pushee, Ian A.)
Abstract We present a video event mining framework that consists of comprehensive set of tools for event detection, annotation, content browsing and a video analysis database. Central to our framework is the video analysis database and the VideoViews database browser that supports both top-down and bottom-up analysis of the video data. to support event mining. We present two methods for video event detection, namely an expert system (CLIPS) rules based approach and a 2-level Hidden Markov Model built upon split and merge behaviors. We devised interfaces for these event detection methods to be operated on the video data in the database for training and detection. We embed scene, object and event data into the video stream as metadata. VideoViews provides interfaces to event detection and video annotation tools. Our video analysis database description scheme represents the structure of the video data from video clips to scenes, objects and their tracks as well as the semantics from simple behaviors to more complex events that may take place over multiple video scenes and/or clips. This framework and the combination of tools enable the users to visualize the raw video data and the processed video information from a number of perspectives facilitating efficient video event mining.
Starting Page 42
Ending Page 42
File Size 520861
Page Count 1
File Format PDF
ISBN 0769519008
ISSN 10636919
DOI 10.1109/CVPRW.2003.10041
Language English
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date 2003-06-16
Publisher Place USA
Access Restriction Subscribed
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword video event detection Event detection Databases Biological system modeling Hidden Markov models Cameras Video event mining video data mining video database navigation Data mining Expert systems video metadata
Content Type Text
Resource Type Article
Subject Computer Vision and Pattern Recognition Software
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