On analyzing video with very small motions

Authors:
M. Dixon;A. Abrams;N. Jacobs;R. Pless
Affiliations:
Washington Univ. in St Louis, St. Louis, MO, USA;Washington Univ. in St Louis, St. Louis, MO, USA;Univ. of Kentucky, Lexington, KY, USA;Washington Univ. in St Louis, St. Louis, MO, USA
Venue:
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Year:
2011

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Abstract

We characterize a class of videos consisting of very small but potentially complicated motions. We find that in these scenes, linear appearance variations have a direct relationship to scene motions. We show how to interpret appearance variations captured through a PCA decomposition of the image set as a scene-specific non-parametric motion basis. We propose fast, robust tools for dense flow estimates that are effective in scenes with small motions and potentially large image noise. We show example results in a variety of applications, including motion segmentation and long-term point tracking.