General highlight detection in sport videos

Ren, R. and Jose, J.M. (2009) General highlight detection in sport videos. In: Advances in Multimedia Modeling. Series: Lecture Notes in Computer Science (5371). Springer: New York, pp. 27-38. ISBN 9783540928911 (doi: 10.1007/978-3-540-92892-8_5)

Abstract

Attention is a psychological measurement of human reflection against stimulus. We propose a general framework of highlight detection by comparing attention intensity during the watching of sports videos. Three steps are involved: adaptive selection on salient features, unified attention estimation and highlight identification. Adaptive selection computes feature correlation to decide an optimal set of salient features. Unified estimation combines these features by the technique of multi-resolution autoregressive (MAR) and thus creates a temporal curve of attention intensity. We rank the intensity of attention to discriminate boundaries of highlights. Such a framework alleviates semantic uncertainty around sport highlights and leads to an efficient and effective highlight detection. The advantages are as follows: (1) the capability of using data at coarse temporal resolutions; (2) the robustness against noise caused by modality asynchronism, perception uncertainty and feature mismatch; (3) the employment of Markovian constrains on content presentation, and (4) multi-resolution estimation on attention intensity, which enables the precise allocation of event boundaries.

• Item Type: Book Sections
• Additional Information: Presented at ACM Multimedia Modelling 2009 in Nice, France 7-9, Jan, 2009
• Keywords: highlight detection, attention computation, sports video analysis
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Ren, Dr Reede
• Authors: Ren, R., and Jose, J.M.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: Springer
• ISBN: 9783540928911
• Copyright Holders: Copyright © 2009 Springer
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher.