Fast Motion Consistency Through Matrix Quantization

Pyry K. Matikainen, Martial Hebert, Rahul Sukthankar, and Yan Ke
Proceedings of the British Machine Vision Conference, September, 2008, pp. 1055-1064.


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Abstract
Determining the motion consistency between two video clips is a key component for many applications such as video event detection and human pose estimation. Shechtman and Irani recently proposed a method for measuring the motion consistency between two videos by representing the motion about each point with a space-time Harris matrix of spatial and temporal derivatives. A motion-consistency measure can be accurately estimated without explicitly calculating the optical flow from the videos, which could be noisy. However, the motion consistency calculation is computationally expensive and it must be evaluated between all possible pairs of points between the two videos. We propose a novel quantization method for the space-time Harris matrices that reduces the consistency calculation to a fast table lookup for any arbitrary consistency measure. We demonstrate that for the continuous rank drop consistency measure used by Shechtman and Irani, our quantization method is much faster and achieves the same accuracy as the existing approximation.

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Number of pages: 10

Text Reference
Pyry K. Matikainen, Martial Hebert, Rahul Sukthankar, and Yan Ke, "Fast Motion Consistency Through Matrix Quantization," Proceedings of the British Machine Vision Conference, September, 2008, pp. 1055-1064.

BibTeX Reference
@inproceedings{Matikainen_2008_6198,
   author = "Pyry K. Matikainen and Martial Hebert and Rahul Sukthankar and Yan Ke",
   editor = "M. Everingham, C. J. Needham, R. Fraile",
   title = "Fast Motion Consistency Through Matrix Quantization",
   booktitle = "Proceedings of the British Machine Vision Conference",
   pages = "1055-1064",
   month = "September",
   year = "2008",
}