Table of Contents
ISRN Machine Vision
Volume 2012, Article ID 959508, 8 pages
http://dx.doi.org/10.5402/2012/959508
Research Article

An Effective Slow-Motion Detection Approach for Compressed Soccer Videos

Machine Vision Laboratory, Computer Engineering Department, Ferdowsi University of Mashhad, Mashhad 9177948944, Iran

Received 21 December 2011; Accepted 15 January 2012

Academic Editors: M. Pardàs and A. Prati

Copyright © 2012 Vahid Kiani and Hamid Reza Pourreza. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.