Extraction and classification of self-consumable sport video highlights using generic HMM


Autoria(s): Tjondronegoro, Dian; Chen, Yi-Ping Phoebe; Pham, Binh
Contribuinte(s)

Rhee, S. B.

Data(s)

01/01/2005

Resumo

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 HMMbased 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.<br />

Identificador

http://hdl.handle.net/10536/DRO/DU:30009701

Idioma(s)

eng

Publicador

IEEE Computer Society Press

Relação

http://dro.deakin.edu.au/eserv/DU:30009701/chen-extractionandclassification-2005.pdf

http://eprints.qut.edu.au/4940/1/4940_1.pdf

Direitos

2005, IEEE

Palavras-Chave #self-consumable highlights #sport video summarization #Hidden Markov Model (HMM) #audiovisual features
Tipo

Conference Paper