3 research outputs found
Depth map compression via 3D region-based representation
In 3D video, view synthesis is used to create new virtual views between
encoded camera views. Errors in the coding of the depth maps introduce
geometry inconsistencies in synthesized views. In this paper, a new 3D plane
representation of the scene is presented which improves the performance of
current standard video codecs in the view synthesis domain. Two image segmentation
algorithms are proposed for generating a color and depth segmentation.
Using both partitions, depth maps are segmented into regions without
sharp discontinuities without having to explicitly signal all depth edges. The
resulting regions are represented using a planar model in the 3D world scene.
This 3D representation allows an efficient encoding while preserving the 3D
characteristics of the scene. The 3D planes open up the possibility to code
multiview images with a unique representation.Postprint (author's final draft
Depth map coding using graph based transform and transform domain sparsification
Depth map compression is important for compact “texture-plus-depth” representation of a 3D scene, where texture and depth maps captured from multiple camera viewpoints are coded into the same format. Having received such format, the decoder can synthesize any novel intermediate view using texture and depth maps of two neighboring captured views via depth-image-based rendering (DIBR). In this paper, we combine two previously proposed depth map compression techniques that pro-mote sparsity in the transform domain for coding gain—graph-based transform (GBT) and transform domain sparsification (TDS)—together under one unified optimization framework. The key to combining GBT and TDS is to adaptively select the sim-plest transform per block that leads to a sparse representation. For blocks without detected prominent edges, the synthesized view’s distortion sensitivity to depth map errors is low, and TD