WIAMIS '07 Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services
Content-based Table Tennis Games Highlight Detection Utilizing Audiovisual Clues
ICIG '07 Proceedings of the Fourth International Conference on Image and Graphics
A Logic Framework for Sports Video Summarization Using Text-Based Semantic Annotation
SMAP '08 Proceedings of the 2008 Third International Workshop on Semantic Media Adaptation and Personalization
ICCEE '08 Proceedings of the 2008 International Conference on Computer and Electrical Engineering
Event-Based Soccer Video Retrieval with Interactive Genetic Algorithm
ISISE '08 Proceedings of the 2008 International Symposium on Information Science and Engieering - Volume 02
Semantic scene detection system for baseball videos based on the MPEG-7 specification
Proceedings of the 2010 ACM Symposium on Applied Computing
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Automatic player behavior analyses from baseball broadcast videos
AMT'12 Proceedings of the 8th international conference on Active Media Technology
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In this paper, we proposed an event detection method in baseball videos based on a multi-output HMM (hidden Markov model), using high-level audio/video features. For the video part, we use eight kinds of semantic scenes detected from baseball videos in our previous work. For the audio part, we extract the audio shots from corresponding video scenes, and cut an audio shot into N one-second clips. Then, the MFCC and ZCR of a one-second clip are extracted and fed into the SVM for classifying it as "acclaim" and "silence". Based on the classification results, the type of an audio shot can be determined in the post-classification. Next, a multi-output HMM modified from the original HMM is used to combine video and audio features to detect baseball video events. Finally, the experimental results show, the multi-output HMM has good event detection accuracy.