The Hierarchical Hidden Markov Model: Analysis and Applications
Machine Learning
The Holy Grail of Content-Based Media Analysis
IEEE MultiMedia
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Automatic Parsing of TV Soccer Programs
ICMCS '95 Proceedings of the International Conference on Multimedia Computing and Systems
Dynamic bayesian networks: representation, inference and learning
Dynamic bayesian networks: representation, inference and learning
A mid-level representation framework for semantic sports video analysis
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Semantic annotation of soccer videos: automatic highlights identification
Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
Sports Video Mining with Mosaic
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Selection of Generative Models in Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive estimation of generative models of video
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Camera View-Based American Football Video Analysis
ISM '06 Proceedings of the Eighth IEEE International Symposium on Multimedia
ClassView: hierarchical video shot classification, indexing, and accessing
IEEE Transactions on Multimedia
Semantic Image and Video Indexing in Broad Domains
IEEE Transactions on Multimedia
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
Video summarization and scene detection by graph modeling
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
Automatic summarization of cricket video events using genetic algorithm
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Finding the game flow from sports video
J-MRE '11 Proceedings of the 2011 joint ACM workshop on Modeling and representing events
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We study sports video mining as a machine learning and statistical inference problem. We focus on mid-level semantic structures that can serve as building blocks for high-level semantic analysis. Particularly, we are interested in how to infer multiple coexistent structures jointly. We present a new multichannel segmental hidden Markov model (MCSHMM) that is a unique probabilistic graphical model with two advantages. One is the integration of both hierarchical and parallel dynamic structures that offers more flexibility and capacity of capturing the interaction between multiple Markov chains. The other is the incorporation of the segmental HMM (SHMM) to deal with variable-length observations. In addition, we develop a maximum a posteriori (MAP) estimator to optimize the model structure and parameters simultaneously. The proposed MCSHMM is used for American football video analysis. The experiment result shows that the MCSHMM outperforms existing HMMs and has potential to be extended for other video mining tasks.