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.
Highlights
Video can be defined as an audio-visual information type
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 employs FD differences of consecutive video frames to detect the shot transitions where roughness of image intensity surface and textural information of video frames are taken into consideration
Summary
Video can be defined as an audio-visual information type. With the rapid advances on communication technology, computer performance and storage media, video is available on various applications such as internet conferencing, multimedia authoring systems, eeducation and video-on-demand systems. Shot transition detection, which is an important part of scene extraction job, is carried out by pixel-difference based motion intensity method with simple threshold approach. The proposed shot transition detection method utilizes FD difference (FDD) values of consecutive video frames. In addition to getting benefit from FD information of video frames in shot transition detection, this study (originated from [20]) offers additional novelties and improvements with respect to [19]. FD values are estimated from sub-regions of video frames In this way, locations of the shot transitions are emphasized much clearly. Organization of the rest of the paper is as follows: Section 2 summarizes the pixel and histogram based shot transition detection approaches that are available in the literature.
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