Extraction and Classification of Self-consumable Sport Video Highlights Using Generic HMM
Dian Tjondronegoro, Yi‐Ping Phoebe Chen, Binh Pham · Deakin Research Online (Deakin University) · 2005
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. Keywords: Self-consumable highlights, sport video summarization, Hidden Markov Model (HMM), audio-visual features.