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Trajectory representation using Gabor features for motion-based video retrieval
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AI
DOI：10.1016/j.patrec.2009.04.003.png)
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This paper proposes a Gabor filter based representation of motion trajectory, for the purpose of motion-based video retrieval. We propose a spectro-temporal representation of the trajectory, which involves the process of detecting a set of salient points from the peaks (locally) of the Gabor filter responses. The change in trajectory direction is also represented by observing the clockwise or anti-clockwise change in direction at the salient points. The feature set (formed by the frequency, temporal location and turning direction at each salient point) provides a semantic representation of the trajectory. Our approach is a global trajectory representation where matching is performed based on edit distance and is shown to perform well even for partial trajectory matching. The system is tested using two benchmark databases of trajectories, as well as various hand-drawn and partial trajectories. We have also experimented on real world videos. Experimental results have shown better performance than existing systems based on Fourier descriptors, polynomial representation and two state-of-the-art methods of symbolic representations based on PCA and characteristics of movement. (C) 2009 Elsevier B.V. All rights reserved.
Keyword:
Trajectory representation
Spectral features
Gabor filters
Partial trajectory matching
Edit distance
Motion-based video retrieval
期刊
IF:
3.3
论文数:
7.9K
被引数:
1.6W
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