A shot classification method of selecting effective key-frames for video browsing
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Content-based retrieval of video data with flexibly managed attributes
Knowledge and Information Systems
An integrated baseball digest system using maximum entropy method
Proceedings of the tenth ACM international conference on Multimedia
Extracting Semantic Information from Basketball Video Based on Audio-Visual Features
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Multimedia Tools and Applications
Maximum entropy model-based baseball highlight detection and classification
Computer Vision and Image Understanding - Special issue on event detection in video
Query by image and video content: a colored-based stochastic model approach
Data & Knowledge Engineering
Audio keywords generation for sports video analysis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Content-based scene segmentation scheme for efficient multimedia information retrieval
International Journal of Wireless and Mobile Computing
Audio-based event detection for sports video
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
A semi-automatic feature selecting method for sports video highlight annotation
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Journal of Signal Processing Systems
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Audio visual cues for video indexing and retrieval
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
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In this paper we study an important problem in multimedia database, namely, the automatic extraction of indexing information from raw data based on video contents. The goal of our research project is to develop a prototype system for automatic indexing of sports videos. The novelty of our work is that we propose to integrate speech understanding and image analysis algorithms for extracting information. The main thrust of this work comes from the observation that in news or sports video indexing, usually speech analysis is more efficient in detecting events than image analysis. Therefore, in our system, the audio processing modules are first applied to locate candidates in the whole data. This information is passed to the video processing modules, which further analyze the video. The final products of video analysis are in the form of pointers to the locations of interesting events in a video. Our algorithms have been tested extensively with real TV programs, and results are presented and discussed in the paper.