Rao, C., Gritai, A., Shah, M., and Syeda-Mahmood, T., View-invariant Alignment and Matching of Video Sequences. In ICCV '03: Proceedings of the IEEE International Conference on Computer Vision 2003.
vol. 2, pp.
939
- 945, 2003. ABSTRACT In this paper, we propose a novel method to establish temporal
correspondence between the frames of two videos. 3D epipolar geometry is
used to eliminate the distortion generated by the projection from 3D to
2D. Although the fundamental matrix contains the extrinsic property of
the projective geometry between views, it is sensitive to noise.
Therefore, we propose the use of a rank constraint of corresponding
points in two views to measure the similarity between trajectories. This
rank constraint shows more robustness and avoids computation of the
fundamental matrix. A dynamic programming approach using the similarity
measurement is proposed to find the nonlinear time-warping function for
videos containing human activities. In this way, videos of different
individuals taken at different times and from distinct viewpoints can be
synchronized. A temporal pyramid of trajectories is applied to improve
the accuracy of the view-invariant dynamic time-warping approach. We
show various applications of this approach such as video synthesis,
human action recognition, and computer aider training. Compared to
state-of-the-art techniques, our method shows a great improvement. |
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