Publication: Adaptive Multi-Pattern Fast Block-Matching Algorithm Based on Motion Classification Techniques
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ISSN: 1520-6149
ISBN: 1-4244-0728-1
Publication date
2007
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Tutors
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IEEE
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Abstract
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
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Keywords
image classification, image matching, image sequences, motion estimation, video codecs, adaptive multipattern fast block-matching algorithm, binary linear classifiers, motion classification techniques, time-consuming subsystem, video sequences, Block-matching, binary linear classifier, motion classification
Bibliographic citation
2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2007. Proceedings. ICASSP 2007 pp. I-1177-1180