Audio events detection based highlights extraction from baseball, golf and soccer games in a unified framework

Authors:
Ziyou Xiong;R. Radhakrishnan;A. Divakaran;T. S. Huang
Affiliations:
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA;Sch. of Electr., Comput. & Telecommun. Eng., Wollongong Univ., NSW, Australia;Sch. of Electr., Comput. & Telecommun. Eng., Wollongong Univ., NSW, Australia;Perceptual Interfaces & Reality Lab., Maryland Univ., College Park, MD, USA
Venue:
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Year:
2003

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Abstract

We developed a unified framework to extract highlights from three sports: baseball, golf and soccer by detecting some of the common audio events that are directly indicative of highlights. We used MPEG-7 audio features and entropic prior hidden Markov models (HMM) as the audio features and classifier respectively to recognize these common audio events. Together with pre- and post-processing techniques using general sports knowledge, we have been able to generate promising results dealing with the audio track that is dominated by audio mixtures and noisy background.