Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning in graphical models
Rule-based video classification system for basketball video indexing
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Recognizing planned multiperson action
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Semantic Indexing of Multimedia Documents
IEEE MultiMedia
Automatic Classification of Tennis Video for High-level Content-based Retrieval
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
Event detection and recognition for semantic annotation of video
Multimedia Tools and Applications
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Automatic annotation of semantic events allows effective retrieval of video content. In this work, we present solutions for highlights detection in sports videos. The proposed approach exploits the typical structure of a wide class of sports videos, namely those related to sports which are played in delimited venues with playfields of well known geometry, like soccer, basketball, swimming, track and field disciplines, and so on. For these sports, a modeling scheme based on a limited set of visual cues and on finite state machines that encode the temporal evolution of highlights is presented, that is of general applicability to this class of sports. Visual cues encode position and speed information coming from the camera and from the object/athletes that are present in the scene, and are estimated automatically from the video stream. Algorithms for model checking and for visual cues estimation are discussed, as well as applications of the representation to different sport domains.