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An iterative region‐growing algorithm for motion segmentation and estimation
Author(s) -
Montoliu Raul,
Pla Filiberto
Publication year - 2005
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20082
Subject(s) - a priori and a posteriori , segmentation , motion estimation , artificial intelligence , pixel , computer science , algorithm , sequence (biology) , computer vision , motion (physics) , process (computing) , image segmentation , iterative method , pattern recognition (psychology) , operating system , philosophy , epistemology , biology , genetics
This article presents a new framework for the motion segmentation and estimation task on sequences of two gray images without a priori information of the number of moving regions present in the sequence. The proposed algorithm uses temporal information, by using an accurate Generalized Least‐Squares motion estimation process, and spatial information, by using an iterative region‐growing algorithm that classifies regions of pixels into the different motion models present in the sequence. The initial regions of pixels are obtained from a given gray‐level segmentation process. The performance of the algorithm is tested on synthetic and real images with multiple objects undergoing different types of motion. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 577–590, 2005.