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Motion Entropy Feature and Its Applications to Event-Based Segmentation of Sports Video
EURASIP Journal on Advances in Signal Processing volume 2008, Article number: 460913 (2008)
Abstract
An entropy-based criterion is proposed to characterize the pattern and intensity of object motion in a video sequence as a function of time. By applying a homoscedastic error model-based time series change point detection algorithm to this motion entropy curve, one is able to segment the corresponding video sequence into individual sections, each consisting of a semantically relevant event. The proposed method is tested on six hours of sports videos including basketball, soccer, and tennis. Excellent experimental results are observed.
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Chen, CY., Wang, JC., Wang, JF. et al. Motion Entropy Feature and Its Applications to Event-Based Segmentation of Sports Video. EURASIP J. Adv. Signal Process. 2008, 460913 (2008). https://doi.org/10.1155/2008/460913
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DOI: https://doi.org/10.1155/2008/460913