Automatic partitioning of full-motion video
Multimedia Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure analysis of soccer video with domain knowledge and hidden Markov models
Pattern Recognition Letters - Video computing
Maximum entropy model-based baseball highlight detection and classification
Computer Vision and Image Understanding - Special issue on event detection in video
Learning the semantics of multimedia queries and concepts from a small number of examples
Proceedings of the 13th annual ACM international conference on Multimedia
Machine Learning for Multimedia Content Analysis (Multimedia Systems and Applications)
Machine Learning for Multimedia Content Analysis (Multimedia Systems and Applications)
Video analysis of hockey play in selected game situations
Image and Vision Computing
Shot-boundary detection: unraveled and resolved?
IEEE Transactions on Circuits and Systems for Video Technology
Event detection in field sports video using audio-visual features and a support vector Machine
IEEE Transactions on Circuits and Systems for Video Technology
An ICA Mixture Hidden Markov Model for Video Content Analysis
IEEE Transactions on Circuits and Systems for Video Technology
Extracting semantics from audio-visual content: the final frontier in multimedia retrieval
IEEE Transactions on Neural Networks
Automatic event-based indexing of multimedia content using a joint content-event model
Proceedings of the 2nd ACM international workshop on Events in multimedia
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In this paper we present a new event analysis framework based on mixture Hidden Markov Model(HMM) for ice hockey video. Hockey is a competitive sport, which is hard to model because of its frame color homogeneity. But it does posses many temporal regularities. With the mixture representation of local observations and Markov chain property of hockey event structure the hockey shot event is successfully modeled as a mixture HMM. Based on the mixture HMM the hockey shot event could be classified with higher accuracy. Two kinds of mixture HMM are compared for the real hockey video shot event classification. The results prove our analysis that the mixture HMM is a suitable model to deal with complex videos with intensive activities. The new mixture HMM hockey shot event model could be a very useful tool for coaches and players to analyze hockey games.