Sports video summarization based on motion analysis

Authors:
Engin Mendi;HéLio B. Clemente;Coskun Bayrak
Affiliations:
Department of Computer Engineering, KTO Karatay University, Akabe Mah. Cemil Cicek Caddesi, 42020 Karatay, Konya, Turkey;Department of Computer Science, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR, USA;Department of Computer Science, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR, USA
Venue:
Computers and Electrical Engineering
Year:
2013

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Abstract

Non-annotated video is more common than ever and this fact leads to an emerging field called video summarization. Key frame selection using motion analysis can greatly increase the understanding of the video content by presenting a series of frames summarizing the intended video. In this paper, we present an automatic video summarization technique based on motion analysis. The proposed technique defines motion metrics estimated from two optical flow algorithms, each using two different key frame selection criteria. We conducted a subjective user study to evaluate the performance of the motion metrics. The summarization process is threshold free and experimental results have verified the effectiveness of the method.