WestminsterResearch

An unsupervised method for active region extraction in sports videos

Mentzelopoulos, Markos and Angelopoulou, Anastassia and Psarrou, Alexandra (2011) An unsupervised method for active region extraction in sports videos. In: Cabestany, Joan and Rojas, Ignacio and Joya, Gonzalo, (eds.) Advances in Computational Intelligence: 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Torremolinos-Málaga, Spain, June 8-10, 2011, Proceedings, Part II. Lecture notes in computer science (6692). Springer, pp. 42-49. ISBN 9783642214974

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1007/978-3-642-21498-1_8

Abstract

In this paper, we propose a fully automatic and computationally efficient algorithm for analysis of sports videos. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.

Item Type:Book Section
Research Community:University of Westminster > Electronics and Computer Science, School of
ID Code:9718
Deposited On:15 Sep 2011 12:57
Last Modified:15 Sep 2011 12:59

Repository Staff Only: item control page