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Motion segmentation using curve fitting on Lagrangian particle trajectories

Narayan, Sanath and Ramakrishnan, KR (2012) Motion segmentation using curve fitting on Lagrangian particle trajectories. In: 2012 21st International Conference on Pattern Recognition (ICPR), 11-15 Nov. 2012, Tsukuba.

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In this paper we present a segmentation algorithm to extract foreground object motion in a moving camera scenario without any preprocessing step such as tracking selected features, video alignment, or foreground segmentation. By viewing it as a curve fitting problem on advected particle trajectories, we use RANSAC to find the polynomial that best fits the camera motion and identify all trajectories that correspond to the camera motion. The remaining trajectories are those due to the foreground motion. By using the superposition principle, we subtract the motion due to camera from foreground trajectories and obtain the true object-induced trajectories. We show that our method performs on par with state-of-the-art technique, with an execution time speed-up of 10x-40x. We compare the results on real-world datasets such as UCF-ARG, UCF Sports and Liris-HARL. We further show that it can be used toper-form video alignment.

Item Type: Conference Proceedings
Publisher: IEEE
Additional Information: Copyright of this article belongs to IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 29 May 2013 10:28
Last Modified: 29 May 2013 10:28
URI: http://eprints.iisc.ac.in/id/eprint/46552

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