SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Video parsing and browsing using compressed data
Multimedia Tools and Applications
Automatic text recognition for video indexing
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Omni-face detection for video/image content description
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
3D-List: A Data Structure for Efficient Video Query Processing
IEEE Transactions on Knowledge and Data Engineering
Learning and Feature Selection in Stereo Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
News video classification using SVM-based multimodal classifiers and combination strategies
Proceedings of the tenth ACM international conference on Multimedia
Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods
ECML '93 Proceedings of the European Conference on Machine Learning
Feature selection for high-dimensional genomic microarray data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Feature Selection and Dualities in Maximum Entropy Discrimination
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Extracting Semantic Information from Basketball Video Based on Audio-Visual Features
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Automated Scene Matching in Movies
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Semantic Video Retrieval Using Audio Analysis
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Challenges of Image and Video Retrieval
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Video Retrieval by Feature Learning in Key Frames
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Video OCR: indexing digital new libraries by recognition of superimposed captions
Multimedia Systems - Special section on video libraries
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Editorial introduction: video retrieval and summarization
Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
Sort-merge feature selection and fusion methods for classification of unstructured video
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Similarity retrieval of videos by using 3D C-string knowledge representation
Journal of Visual Communication and Image Representation
Interactive multimedia system for distance learning of higher education
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
Narrative structure analysis of lecture video with hierarchical hidden markov model for e-learning
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
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We present a fast video retrieval system with three novel characteristics. First, it exploits the methods of machine learning to construct automatically a hierarchy of small subsets of features that are progressively more useful for indexing. These subsets are induced by a new heuristic method called Sort-Merge feature selection, which exploits a novel combination of Fastmap for dimensionality reduction and Mahalanobis distance for likelihood determination. Second, because these induced feature sets form a hierarchy with increasing classification accuracy, video segments can be segmented and categorized simultaneously in a coarse-fine manner that efficiently and progressively detects and refines their temporal boundaries. Third, the feature set hierarchy enables an efficient implementation of query systems by the approach of lazy evaluation, in which new queries are used to refine the retrieval index in real-time. We analyze the performance of these methods, and demonstrate them in the domain of a 75-min instructional video and a 30-min baseball video.