Point cloud estimation for 3D structure-based frame prediction in video coding

PubDate: August 2017

Teams: RWTH Aachen University

Writers: Hossein Bakhshi Golestani ; Jens Schneider ; Mathias Wien ; Jens-Rainer Ohm

PDF: Point cloud estimation for 3D structure-based frame prediction in video coding

Abstract

3D scene reconstruction from multi-view images has many practical applications, including games, virtual/augmented reality, and digital archives of cultural heritage. In this paper, we introduce a new application in video compression. The proposed idea is to have the decoder reconstruct a 3D scene model based on a subset of decoded frames and then reproject the 3D model to 2D for prediction or reconstruction of intermediate and/or future frames; this can also include a further motion compensation step in 2D. Structure from Motion (SfM) has been employed as a tool to estimate 3D point clouds and camera parameters. This approach has been integrated to generate additional reference pictures in an HEVC codec, and was tested so far on two 4K video sequences: A computer generated sequence with moving objects and a natural but stationary scene captured from a moving camera. Initial simulation results show around 0.8% bit-rate reduction compared to HEVC Test Model (HM16.7). It is asserted that the method offers headroom for further improvements by enhancing the reconstruction algorithms.