An Effective Slow-Motion Detection Approach for Compressed Soccer Videos | Zendy

Vahid Kiani | Zendy; Hamid Reza Pourreza | Zendy

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An Effective Slow-Motion Detection Approach for Compressed Soccer Videos

Author(s) -

Vahid Kiani,

Hamid Reza Pourreza

Publication year - 2012

Publication title -

isrn machine vision

Language(s) - English

Resource type - Journals

eISSN - 2090-780X

pISSN - 2090-7796

DOI - 10.5402/2012/959508

Subject(s) - computer science , artificial intelligence , computer vision , motion (physics) , decoding methods , shot (pellet) , support vector machine , set (abstract data type) , quarter pixel motion , slow motion , bitstream , motion vector , image (mathematics) , algorithm , art , chemistry , organic chemistry , visual arts , programming language

Slow-motion replays are content full segments of broadcast soccer videos. In this paper, we propose an efficient method for detection of slow-motion shots produced by high-speed cameras in soccer broadcasts. A rich set of color, motion, and cinematic features are extracted from compressed video by partial decoding of the MPEG-1 bitstream. Then, slow-motion shots are modeled by SVM classifiers for each shot class. A set of six full-match soccer games is used for training and evaluation of the proposed method. Our algorithm presents satisfactory results along with high speed for slow-motion detection in soccer videos.

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