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Robust Tracking in Aerial Imagery Based on an Ego-Motion Bayesian Model
Blanco Adán, Carlos Roberto del and Jaureguizar Núñez, Fernando and García Santos, Narciso
Robust Tracking in Aerial Imagery Based on an Ego-Motion Bayesian Model.
"EURASIP Journal on Advances in Signal Processing", v. 2010
A novel strategy for object tracking in aerial imagery is presented, which is able to deal with complex situations where the camera ego-motion cannot be reliably estimated due to the aperture problem (related to low structured scenes), the strong ego-motion, and/or the presence of independent moving objects. The proposed algorithm is based on a complex modeling of the dynamic information, which simulates both the object and the camera dynamics to predict the putative object locations. In this model, the camera dynamics is probabilistically formulated as a weighted set of affine transformations that represent possible camera ego-motions. This dynamic model is used in a Particle Filter framework to distinguish the actual object location among the multiple candidates, that result from complex cluttered backgrounds, and the presence of several moving objects. The proposed strategy has been tested with the aerial FLIR AMCOM dataset, and its performance has been also compared with other tracking techniques to demonstrate its efficiency.
Doctor Carlos Roberto del Blanco Adán
||27 May 2011 11:42
||20 Apr 2016 16:27
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