Fractal Dimension Based Shot Transition Detection in Sport Videos

Abstract

Increase in application fields of video has boosted the demand to analyze and organize video libraries for efficient scene analysis and information retrieval. This paper addresses the detection of shot transitions, which plays a crucial role in scene analysis, using a novel method based on fractal dimension (FD) that carries information on roughness of image intensity surface and textural structure. The proposed method is tested on sport videos including soccer and tennis matches that contain considerable amount of abrupt and gradual shot transitions. Experimental results indicate that the FD based shot transition detection method offers promising performance with respect to pixel and histogram based methods available in the literature

Shot-change detection based on multifractal analysis

“…Depending on different low level features which are used, detection techniques can be based on differences of pixel values [2], histogram differences [3], edges [4], motion features [5], the second order statistics [5] and MPEG statistics [6]. New detection techniques of abrupt shot changes based on Wavelets [7] and fractals [8] have recently appeared in literature. Low-level features can be extracted in spatial domain on pixel level [5], on the regional level [4], [9], and for the entire frame [10], [11].…”