Attribute-based people search in surveillance environments
Daniel A. Vaquero, Rogerio S. Feris, et al.
WACV 2009
Matching Pursuit decomposes a signal into a linear expansion of functions selected from a redundant dictionary, isolating the signal structures that are coherent with respect to a given dictionary. In this paper we focus on the Matching Pursuit representation of the displaced frame difference (dfd). In particular, we introduce a new dictionary for Matching Pursuit that efficiently exploits the signal structures of the dfd. We also propose a fast strategy to find the atoms exploiting the max of the absolute value of the error in the motion predicted image and the convergence of the MSE with the rotation of the atoms. Results show that the fast strategy is quite robust when compared to exhaustive search techniques and it improves the results of a suboptimal search strategy based on a genetic algorithm.
Daniel A. Vaquero, Rogerio S. Feris, et al.
WACV 2009
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
Pavel Kisilev, Daniel Freedman, et al.
ICPR 2012
Sudeep Sarkar, Kim L. Boyer
Computer Vision and Image Understanding