Shot-change detection based on multifractal analysis

This paper presents a new algorithm for detection of abrupt shot changes in video sequence based on Multifractal Analysis (MA). Video sequence is decoded into series of frames, and low level feature for texture and color are extracted from each of them. Content difference between adjacent frames is calculated based on correlation of frame low level features. MA is used for description of content difference arrays in multifractal singularity domain (α - domain) with emphasized local singularities. The detection of abrupt changes is realized using fixed thresholds technique and singularity shape analysis. Proposed algorithm is tested on more than 600 000 frames, with high efficiency of detection.