Motion estimation is the most time-consuming subsystem in a video codec. Thus, more efficient methods of motion estimation should be investigated. Real video sequences usually exhibit a wide-range of motion content as well as different degrees of detail, which become particularly difficult to manage by typical block-matching algorithms. Recent developments in the area of motion estimation have focused on the adaptation to video contents. Adaptive thresholds and multi-pattern search algorithms have shown to achieve good performance when they success to adjust to motion characteristics. This paper proposes an adaptive algorithm, called MCS, that makes use of an especially tailored classifier that detects some motion cues and chooses the search pattern that best fits to them. Specifically, a hierarchical structure of binary linear classifiers is proposed. Our experimental results show that MCS notably reduces the computational cost with respect to an state-of-the-art method while maintaining the quality ; Publicado
Adaptive Multi-Pattern Fast Block-Matching Algorithm Based on Motion Classification Techniques
2007-01-01
Conference paper
Electronic Resource
English
binary linear classifiers , video sequences , image sequences , video codecs , Telecomunicaciones , motion estimation , Block-matching , time-consuming subsystem , binary linear classifier , motion classification techniques , image matching , adaptive multipattern fast block-matching algorithm , motion classification , image classification
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