Abstract:

In this paper, we present a coding framework addressing the compression of dynamic 3D point clouds which represent real world objects and which result from a video acquisiton using multiple cameras. The encoding is performed as an off-line process and is not time-critical. The decoding however, must allow for real-time rendering of the dynamic 3D point cloud. We introduce a compression framework which encodes multiple attributes like depth and color of 3D video fragments into progressive streams. The reference data structure is alighned on the original camera input images and thus allows for easy view-dependent decoding. The separate encoding of the object\'s silhouette allows the use of shape-adaptive compression algorithms. A novel differential coding approach permits random access in constant time throughout the complete data set and thus enables true free viewpoint video.