Automatic detection of 'Goal' segments in basketball videos
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Content-Based Retrieval of Video Data Based on Spatiotemporal Correlation of Objects
ICMCS '98 Proceedings of the IEEE International Conference on Multimedia Computing and Systems
A highly efficient system for automatic face region detection in MPEG video
IEEE Transactions on Circuits and Systems for Video Technology
The fusion of audio-visual features and external knowledge for event detection in team sports video
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Fusion of AV features and external information sources for event detection in team sports video
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Content-aware video adaptation under low-bitrate constraint
EURASIP Journal on Advances in Signal Processing
A novel block intensity comparison code for video classification and retrieval
Expert Systems with Applications: An International Journal
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This paper presents an edge-based semantic classification of sports video sequences. The paper presents an algorithm for edge detection, and illustrates the usage of edges for semantic analysis of video content. We first propose an algorithm for detecting edges within video frames directly on the MPEG format without a decompression process. The algorithm is based on a spatial-domain synthetic edge model, which is defined using interrelationship of two DCT edge features: horizontal and vertical. We then use a multi-step approach to classify video sequences into meaningful semantic segments such as "goal", "foul", and "crowd" in basketball games using the "edgeness" criteria. We then show how an audio feature ("whistles") can be used as a filter to enhance edge-based semantic classification.