Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Rule-based video classification system for basketball video indexing
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Semantic Annotation of Sports Videos
IEEE MultiMedia
Applications of Video-Content Analysis and Retrieval
IEEE MultiMedia
Efficient Multimodal Features for Automatic Soccer Highlight Generation
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
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
On the detection of semantic concepts at TRECVID
Proceedings of the 12th annual ACM international conference on Multimedia
Sports Video Mining with Mosaic
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Video Data Mining: Semantic Indexing and Event Detection from the Association Perspective
IEEE Transactions on Knowledge and Data Engineering
An Integrated Framework for Semantic Annotation and Adaptation
Multimedia Tools and Applications
Canny Edge Detection Enhancement by Scale Multiplication
IEEE Transactions on Pattern Analysis and Machine Intelligence
HMM based structuring of tennis videos using visual and audio cues
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Semantic concept extraction from sports video for highlight generation
MobiMedia '06 Proceedings of the 2nd international conference on Mobile multimedia communications
Audio-based event detection for sports video
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
A hierarchical framework for generic sports video classification
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Personalized abstraction of broadcasted American football video by highlight selection
IEEE Transactions on Multimedia
Joint scene classification and segmentation based on hidden Markov model
IEEE Transactions on Multimedia
A unified framework for semantic shot classification in sports video
IEEE Transactions on Multimedia
Adaptive extraction of highlights from a sport video based on excitement modeling
IEEE Transactions on Multimedia
Fusion of audio and motion information on HMM-based highlight extraction for baseball games
IEEE Transactions on Multimedia
Generation of Personalized Music Sports Video Using Multimodal Cues
IEEE Transactions on Multimedia
Human Behavior Analysis for Highlight Ranking in Broadcast Racket Sports Video
IEEE Transactions on Multimedia
Editorial: Introduction to the Special Issue on Multimedia Data Mining
IEEE Transactions on Multimedia
IEEE Transactions on Consumer Electronics
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Automatic summarization of cricket video events using genetic algorithm
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Bayesian belief network based broadcast sports video indexing
Multimedia Tools and Applications
Proceedings of the CUBE International Information Technology Conference
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This paper presents a novel approach towards automated highlight generation of broadcast sports video sequences from its extracted events and semantic concepts. A sports video is hierarchically divided into temporal partitions namely, megaslots, slots, and semantic entities, namely concepts, and events. The proposed method extracts event sequence from video and classifies each sequence into a concept by sequential association mining. The extracted concepts and events within the concepts are selected according to their degree of importance to include those in the highlights. A parameter degree of abstraction is proposed, which gives a choice to the user about how concisely the extracted concepts should be produced for a specified highlight duration. We have successfully extracted highlights from recorded video of cricket match and compared our results with the manually-generated highlights by sports television channel.