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Activity Recognition Using A Mixture of Vector Fields

Nascimento, J. ; Figueiredo, M. A. T. ; Marques, J. S.

IEEE Transactions on Image Processing Vol. 22, Nº 5, pp. 1712 - 1725, May, 2013.

ISSN (print): 1057-7149
ISSN (online):

Journal Impact Factor: 3,315 (in 2008)

Digital Object Identifier: 10.1109/TIP.2012.2226899

Abstract
The analysis of moving objects in image sequences (video) has been one of the major themes in computer vision. In this paper, we focus on video-surveillance tasks; more specifically, we consider pedestrian trajectories and propose modeling them through a small set of motion/vector fields together with a space-varying switching mechanism. Despite the diversity of motion patterns that can occur in a given scene, we show that it is often possible to find a relatively small number of typical behaviors, and model each of these behaviors by a “simple” motion field. We increase the expressiveness of the formulation by allowing the trajectories to switch from one motion field to another, in a space-dependent manner. We present an expectation-maximization algorithm to learn all the parameters of the model, and apply it to trajectory classification tasks. Experiments with both synthetic and real data support the claims about the performance of the proposed approach.