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Particle Video: Long-Range Motion Estimation Using Point Trajectories

Authors
  • Sand, Peter1
  • Teller, Seth1
  • 1 MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, 02139, USA , Cambridge (United States)
Type
Published Article
Journal
International Journal of Computer Vision
Publisher
Springer-Verlag
Publication Date
May 10, 2008
Volume
80
Issue
1
Identifiers
DOI: 10.1007/s11263-008-0136-6
Source
Springer Nature
Keywords
License
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Abstract

This paper describes a new approach to motion estimation in video. We represent video motion using a set of particles. Each particle is an image point sample with a long-duration trajectory and other properties. To optimize particle trajectories we measure appearance consistency along the particle trajectories and distortion between the particles. The resulting motion representation is useful for a variety of applications and cannot be directly obtained using existing methods such as optical flow or feature tracking. We demonstrate the algorithm on challenging real-world videos that include complex scene geometry, multiple types of occlusion, regions with low texture, and non-rigid deformations.

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