In this paper, we overview tracking methods of 3D occluded objects in 3D integral imaging. Two methods based on
Summation of Absolute Difference (SAD) algorithm and Bayesian framework, respectively, are presented. For the
tracking method based on SAD, we calculate SAD between pixels of consecutive frames of a moving object for 3D
tracking. For the tracking method based on Bayesian framework, posterior probabilities of the reconstructed scene
background and the 3D objects are calculated by defining their pixel intensities as Gaussian and Gamma distributions,
respectively, and by assuming appropriate prior distributions for estimated parameters. Multi-objects tracking is
achieved by maximizing the geodesic distance between the log-likelihood of the background and the objects.
Experimental results demonstrate 3D tracking of occluded objects.