Extraction and Classification of Self-consumable Sport Video Highlights Using Generic HMM
Tjondronegoro, Dian W., Chen, Yi-Ping Phoebe, & Pham, Binh L. (2005) Extraction and Classification of Self-consumable Sport Video Highlights Using Generic HMM. In 4th Asia Pacific International Symposium on Information Technology, 26-27 January 2005, Gold Coast, Australia.
This paper aims to automatically extract and classify self-consumable sport video highlights. For this purpose, we will emphasize the benefits of using play-break sequences as the effective inputs for HMM-based classifier. HMM is used to model the stochastic pattern of high-level states during specific sport highlights which correspond to the sequence of generic audio-visual measurements extracted from raw video data. This paper uses soccer as the domain study, focusing on the extraction and classification of goal, shot and foul highlights. The experiment work which uses183 play-break sequences from 6 soccer matches will be presented to demonstrate the performance of our proposed scheme.
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|Item Type:||Conference Paper|
|Keywords:||Self, consumable highlights, sport video summarization, Hidden Markov Model (HMM), audio, visual features|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTER SOFTWARE (080300) > Multimedia Programming (080305)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2005 (please consult author)|
|Deposited On:||06 Sep 2006|
|Last Modified:||29 Feb 2012 13:13|
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