Wyner-ziv coding for depth maps in multiview video-plus-depth

Abstract

Three dimensional digital video services are gathering a lot of attention in recent years, thanks to the introduction of new and efficient acquisition and rendering devices. In particular, 3D video is often represented by a single view and a so called depth map, which gives information about the distance between the point of view and the objects. This representation can be extended to multiple views, each with its own depth map.Efficient compression of this kind of data is of course a very important topic in sight of a massive deployment of services such as 3D-TV and FTV (free viewpoint TV). In this paper we consider the application of distributed coding techniques to the coding of depth maps, in order to reduce the complexity of single view or multi view encoders and to enhance interactive multiview video streaming. We start from state-of-the-art distributed video coding techniques and we improve them by using high order motion interpolation and by exploiting texture motion information to encode the depth maps. The experiments reported here show that the proposed method achieves a rate reduction up to 11.06% compared to state-of-the-art distributed video coding technique.

Distributed multi-hypothesis coding of depth maps using texture motion information and optical flow

“…The same concepts can be exploited in a DVC decoder for accurate SI generation, as done in [12] in which multiple decoded texture frames are used. In our work we suppose that the decoder has access to the corresponding texture frame of the to-be-decoded depth frame, while in [12] only the texture frames corresponding to the depth KFs are used. Moreover, we investigate opticalflow-based methods, while [12] investigate only block-based methods.…”

“…In our work we suppose that the decoder has access to the corresponding texture frame of the to-be-decoded depth frame, while in [12] only the texture frames corresponding to the depth KFs are used. Moreover, we investigate opticalflow-based methods, while [12] investigate only block-based methods. The multi-hypothesis decoder employed is the same as in [9] where OBMC was used with block-based extrapolation and optical flow-based interpolation in order to improve a texture-based DVC decoder.…”

A distributed video coding system for multi view video plus depth

“…At the best of our knowledge, this information has been rarely used for the side information generation in DVC applied to multiview video plus depth. Some works [9][10][11] about DVC applied to multiview video plus depth have only highlighted the advantage of sharing the motion information between texture and depth. In a previous work [12], DVC is applied to MVD in order to assure continuity of the playback in the context of the interactive multiview video streaming paradigm.…”

Wyner-Ziv coding of depth maps exploiting color motion information

“…Color Depth t t-1 t+1 If depth and color edges are perfectly aligned, the corresponding Motion Vectors (MVs) present similar behavior 9 . We exploit this fact in order to effectively predict Dt: first MVs between frames Ct and Ct-1, and between Ct and Ct+1 are calculated.…”