Geometric mapping assisted multi-view depth video coding

Qiong Liu, Yongbing Zhang, Xiangyang Ji, Qionghai Dai

Abstract: Multi-view plus depth (MVD), as a video representation supporting view synthesis based on depth video, has attracted more and more attention for the free view video (FVV) application. It is a challenge to efficiently compress the multi-view depth data in MVD format. In this paper, we explore the geometric relationships in 3D space and propose a geometric mapping assisted (GMA) multi-view depth video coding algorithm. The proposed GMA utilizes the mapped depth image as a reference candidate during prediction. Furthermore, the inpainting method is employed to fill in the holes in mapped depth images. Experimental results demonstrate the gains of up to 2.45 dB for the depth coding, as well as better quality of synthesized views.