Motion representation using composite energy features
Pattern Recognition
Generalized least squares-based parametric motion estimation
Computer Vision and Image Understanding
Spatio-temporal composite-features for motion analysis and segmentation
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
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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.