Context modeling based depth image compression for distributed virtual environment

Depth images, comprising pixel intensities and depth map, are viewed as a compact model of 3D scenes and used in 3D image warping for the distributed or collaborative virtual environment to enable the distributed rendering of complex 3D scenes at relatively low cost. The major overhead of the model is the transmission of the depth images of the initial reference and the subsequent new views that may be up to a few Mbs in size depending on the screen resolution. This paper presents efficient compression techniques specifically designed for the depth images. Additionally we experiment with the warped image quality by reducing the resolution of the depth map. We show that significant compression can be achieved at a cost of a very modest impairment in the perceptual quality of the warped image.