Exploiting depth information for fast motion and disparity estimation in Multi-view Video Coding

Abstract

Multi-view Video Coding (MVC) employs both motion and disparity estimation within the encoding process. These provide a significant increase in coding efficiency at the expense of a substantial increase in computational requirements. This paper presents a fast motion and disparity estimation technique that utilizes the multi-view geometry together with the depth information and the corresponding encoded motion vectors from the reference view, to produce more reliable motion and disparity vector predictors for the current view. This allows for a smaller search area which reduces the computational cost of the multi-view encoding system. Experimental results confirm that the proposed techniques can provide a speed-up gain of up to 4.2 times, with a negligible loss in the rate-distortion performance for both the color and the depth MVC.

Low complexity disparity estimation for immersive 3D video transmission

“…This fast disparity estimation technique can also be used with our fast geometric motion estimation techniques, proposed in [19][20][21], to finally obtain a low-computational multi-view video encoder, adequate for low-latency 3DV coding.…”

“…The smallest distortions are normally obtained from the corresponding multi-view areas, as they represent the same object in the viewpoint reference frames [17]. Hence, usually searching only around these similar areas can significantly reduce the exhaustive search and its computational time [9,[18][19][20][21]. These areas can be identified through the multi-view geometry [17] and the average depth value of the current sub-MB to estimate, with the depth values obtained from the depth map MVV.…”

“…Then the search area along the line can be varied from ±3 pels up-to ±10 pels depending on the largest depth change within the sub-MB to encode. If this search area exceeds the value of 10 pixel elements, then it is clipped, since this search area demonstrated to be large enough to use with geometric disparity estimation, to maintain coding efficiency [18][19][20]. Thus, it follows as:…”

Fast inter-mode decision in multi-view video plus depth coding

“…Then, it utilizes its encoded mode and motion vectors to determine the potential optimal modes for the currently being encoded MB, such that only the appropriate sub-optimal modes are tested for Rate Distortion Optimization (RDO). Results show that the technique can save up to about 70% of the encoding time required for the previous estimation techniques used in [9][10][11]. When compared with the original encoder, this solution together with the geometric estimations can save up to 95% of the original encoding time required to encode an interview predicted view, which finally results in an 84% reduction of the whole MVC time.…”

“…To the knowledge of the authors, exploitation of the geometrical information available from the depth data in MVD, for efficient and faster MVV coding of both the color and the depth MVVs, has only been considered in our previous work [8][9][10][11]. In these, we demonstrated that the multi-view geometry together with the available depth data can be used to identify better search areas for DE [9,10] and ME [11]. Thus, these search areas can be reduced and so their associated computations, decreasing the computational demand with negligible influence on the color and the depth MVC efficiency.…”