An advanced Bayesian model for the visual tracking of multiple interacting objects

被引:0
作者
Carlos R del Blanco
Fernando Jaureguizar
Narciso García
机构
[1] Universidad Politécnica de Madrid,Escuela Técnica Superior de Ingenieros de Telecomunicación
来源
EURASIP Journal on Advances in Signal Processing | / 2011卷
关键词
visual tracking; multiple objects; interacting model; particle filter; Rao-Blackwellization; data association;
D O I
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摘要
Visual tracking of multiple objects is a key component of many visual-based systems. While there are reliable algorithms for tracking a single object in constrained scenarios, the object tracking is still a challenge in uncontrolled situations involving multiple interacting objects that have a complex dynamics. In this article, a novel Bayesian model for tracking multiple interacting objects in unrestricted situations is proposed. This is accomplished by means of an advanced object dynamic model that predicts possible interactive behaviors, which in turn depend on the inference of potential events of object occlusion. The proposed tracking model can also handle false and missing detections that are typical from visual object detectors operating in uncontrolled scenarios. On the other hand, a Rao-Blackwellization technique has been used to improve the accuracy of the estimated object trajectories, which is a fundamental aspect in the tracking of multiple objects due to its high dimensionality. Excellent results have been obtained using a publicly available database, proving the efficiency of the proposed approach.
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