Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of speech recognition
Fundamentals of speech recognition
Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Video Processing and Communications
Video Processing and Communications
An integrated baseball digest system using maximum entropy method
Proceedings of the tenth ACM international conference on Multimedia
Event Detection and Summarization in Sports Video
CBAIVL '01 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'01)
Detection and Description of Human Running Behaviour in Sports Video Multimedia Database
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
Machine Vision: Theory, Algorithms, Practicalities
Machine Vision: Theory, Algorithms, Practicalities
Shot boundary refinement for long transition in digital video sequence
IEEE Transactions on Multimedia
Automatic detection and indexing of video-event shots for surveillance applications
IEEE Transactions on Multimedia
A fast recursive shortest spanning tree for image segmentation and edge detection
IEEE Transactions on Image Processing
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
Summarization of videotaped presentations: automatic analysis of motion and gesture
IEEE Transactions on Circuits and Systems for Video Technology
Performance characterization of video-shot-change detection methods
IEEE Transactions on Circuits and Systems for Video Technology
A semantic event-detection approach and its application to detecting hunts in wildlife video
IEEE Transactions on Circuits and Systems for Video Technology
Shot-boundary detection: unraveled and resolved?
IEEE Transactions on Circuits and Systems for Video Technology
A context-aware middleware for real-time semantic enrichment of distributed multimedia metadata
Multimedia Tools and Applications
Content-based story segmentation of news video by multimodal analysis
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
Content-based scene detection and analysis method for automatic classification of TV sports news
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
A template-based baseball video scene classification using efficient playfield segmentation
Multimedia Tools and Applications
HMM-based ball hitting event exploration system for broadcast baseball video
Journal of Visual Communication and Image Representation
HMM based soccer video event detection using enhanced mid-level semantic
Multimedia Tools and Applications
Video structure analysis for content-based indexing and categorisation of TV sports news
International Journal of Intelligent Information and Database Systems
SensorStream: a semantic real-time stream management system
International Journal of Ad Hoc and Ubiquitous Computing
Automatic player behavior analyses from baseball broadcast videos
AMT'12 Proceedings of the 8th international conference on Active Media Technology
International Journal of Multimedia Data Engineering & Management
Dynamic facial expression analysis based on extended spatio-temporal histogram of oriented gradients
International Journal of Biometrics
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A lot of research has lately been focusing on scene analysis in sport videos. By extracting the semantics of successive frames or segmented shots, various kinds of video scenes may be identified. However, general baseball events, e.g., strikeout and ground outs, are hard to be detected because a general baseball event is composed of a series of video scenes and each scene is further composed of several video shots. Hence, the detection of general baseball events has to be developed in terms of scenes to facilitate the retrieval of the required video clips. To do this, the baseball video is firstly segmented into many video shots. Then, various visual features including the image-based features, object-based features, and global motion are extracted to analyze the semantics for each video shot. Each video shot is then classified into the predefined semantic scenes according to its semantics. Finally, the hidden Markov model (HMM) is applied to detect the general baseball events by regarding the classified scenes as observation symbols. The accuracy analysis for the scene classification and event detection are illustrated with a large amount of video data consisting of several hours of video frames. Experimental results show that the proposed system detects the four kinds of general baseball events with reasonable accuracy.