Reduced-complexity search for video coding geometry partitions using texture and depth data

In this paper, a texture-space geometry partitioning approach is proposed to reduce the computational complexity of searching for geometry partitions for video coding. Additionally, for systems that capture both video and depth data, an enhanced geometry partitioning approach using both texture and depth information is proposed to further improve the partitioning accuracy and reduce the search complexity. Compared with a full-search approach, the proposed geometry partition search approaches achieve about 94% reduction of the encoding time while retaining similar rate-distortion performance.