A fuzzy theoretic approach for video segmentation using syntactic features
Pattern Recognition Letters
Recognition of JPEG compressed face images based on AdaBoost
SAMT'07 Proceedings of the semantic and digital media technologies 2nd international conference on Semantic Multimedia
DCT-Domain image retrieval via block-edge-patterns
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Mining Multilevel Image Semantics via Hierarchical Classification
IEEE Transactions on Multimedia
Association and Temporal Rule Mining for Post-Filtering of Semantic Concept Detection in Video
IEEE Transactions on Multimedia
A highly efficient system for automatic face region detection in MPEG video
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the MPEG-7 standard
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
MPEG-7 visual shape descriptors
IEEE Transactions on Circuits and Systems for Video Technology
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Video content processing and analysis is going through a transition from low-level feature based techniques to high-level semantics based approaches. In this paper, we describe such a transition that low level features are processed to extract four semantic patterns, leading to high-level content analysis for snooker videos. Such extracted semantics and recognised patterns include: (i) full court scenes for snooker match, (ii) close-up view of snooker match; (iii) player's face, and (iv) audience's faces. Experimental results support that the proposed technique works well with snooker videos, providing a significant potential for automatic snooker video processing such as annotation, summarization and editing.