Depth compression via planar segmentation

Abstract

Augmented Reality applications are set to revolutionize the smartphone industry due to the integration of RGB-D sensors into mobile devices. Given the large number of smartphone users, efficient storage and transmission of RGB-D data is of paramount interest to the research community. While there exist Video Coding Standards such as HEVC and H.264/AVC for compression of RGB/texture component, the coding of depth data is still an area of active research. This paper presents a method for coding depth videos, captured from mobile RGB-D sensors, by planar segmentation. The segmentation algorithm is based on Markov Random Field assumptions on depth data and solved using Graph Cuts. While all prior works based on this approach remain restricted to images only and under noise-free conditions, this paper presents an efficient solution to planar segmentation in noisy depth videos. Also presented is a unique method to encode depth based on its segmented planar representation. Experiments on depth captured from a noisy sensor (Microsoft Kinect) shows superior Rate-Distortion performance over the 3D extension of HEVC codec.