Title :
CLUMOC: Multiple Motion Estimation by Cluster Motion Consensus
Author :
Yu, Yinan ; Ren, Weiqiang ; Huang, Yongzhen ; Huang, Kaiqi ; Tan, Tieniu
Author_Institution :
Inst. of Autom., Beijing, China
Abstract :
In this paper, we present techniques for robust multiple motions estimation based on dual consensus via clustering in both the image spatial space and the motion parameter space. Starting from traditional Random Samples Consensus algorithm, we novelly propose the CLUster MOtion Consensus (CLUMOC) to extract robust motions. The proposed algorithm has two advantages: (1), instead of random samples, the CLUMOC employs clustering in initial sample selection, which can remove outliers from correct pairs of motion, (2), CLUMOC automatically decides the number of motions, by employing competition among motion and samples, that each motion needs to compete for matching pairs and each pair of matching competes for motions. The experimental results show that the proposed method is effective and efficient under various situations.
Keywords :
feature extraction; image matching; motion estimation; pattern clustering; random processes; CLUMOC; cluster motion consensus; dual-consensus; image spatial space; matching pairs; motion estimation model; motion parameter space; outlier removal; random samples consensus algorithm; robust motion extraction; Consensus Estimation; Motion Estimation; RANSAC;
Conference_Titel :
Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2499-1
DOI :
10.1109/AVSS.2012.19