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Fast Scene Change Detection Using Macro Block Information and Spatio-temporal Histogram  

Jin, Ju-Kyong (Dept. of Electronic Engineering, Inha University)
Cho, Ju-Hee (Dept. of Electronic Engineering, Inha University)
Jeong, Jae-Hyup (Dept. of Electronic Engineering, Inha University)
Jeong, Dong-Suk (Dept. of Electronic Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.48, no.1, 2011 , pp. 141-148 More about this Journal
Abstract
Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.
Keywords
scene change detection; shot boundary detection; video indexing; graph cut partitioning;
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