A quantitative comparison of two new motion estimation algorithms

Authors:
B. Zhan;P. Remagnino;S. A. Velastin;N. Monekosso;L.-Q. Xu
Affiliations:
Digital Imaging Research Centre, Kingston University, UK;Digital Imaging Research Centre, Kingston University, UK;Digital Imaging Research Centre, Kingston University, UK;Digital Imaging Research Centre, Kingston University, UK;British Telecom Research, Ipswich, UK
Venue:
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Year:
2007

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Abstract

This paper proposes a comparison of two motion estimation algorithms for crowd scene analysis in video sequences. The first method uses the local gradient supported by neighbouring topology constraints. The second method makes use of descriptors extracted from points lying at the maximum curvature along Canny edges. Performance is evaluated using real-world video sequences, providing the reader with a quantitative comparison of the two methods.