Object recognition is one of the key features of most of the computer vision applications performing object tracking in images. This becomes troublesome when these images accompany scene reflections leading to mixed images. This paper handles mixed images acquired by mobile cameras. The authors define the tracking scheme in six steps: (1) the prediction stage of RGB color-cue-based estimation draws samples from the importance prior density; (2) the correction stage of RGB color-cue-based estimation updates the importance weight; (3) the prediction stage of the motion-cue-based estimation draws samples from the importance prior density; (4) the correction stage of motion-cue-based estimation updates the importance weight; (5) the weight of each particle is optimized using maximum likelihood; and (6) the target state is estimated.
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