Variational Bayesian inference for stereo object tracking
In this paper, we deal with object tracking in stereo video sequences. We introduce a Bayesian framework for utilizing the results of any conventional single channel object tracker, in order to accomplish the refinement of the tracking accuracy in the left/right video channel. In this Bayesian framework, a variational Bayesian algorithm is employed to this end, where a priori information about the object displacement (movement) over time is incorporated by means of a prior distribution. This a priori information is obtained in a pre-processing step, in which the object displacement over time is estimated. Experiments demonstrate the efficiency of the proposed post-processing methodology in terms of tracking accuracy.