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Object tracking under complex circumstances remains to be a challenging problem because the appearance of an object can be drastically changed by illumination variations, pose variations and occlusion. This paper proposes an adaptive multiCfeature fusion strategy, in which the target appearance is modeled based on timed motion history image with HSV color histogram feature and edge orientation histogram...
The design and implementation of a particle filter tracking algorithm based on adaptive feature fusion of color histogram and edge orientation histogram is introduced. Experimental results show that the feature fusion tracking algorithm is more robust, especially when the target is moving in a varying environment, compared to that of single feature tracking algorithms. The adoption of two features...
Particle filter is a nonlinear filtering algorithm based on Bayesian estimation, which can well deal with non-linear, non-Gaussian system parameter estimation and state filtering problem. In addition, as it allows integration of a variety of features, it is widely used in target tracking. This paper selects the best two features from color and shape-texture features according to their abilities of...
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