CODING-ORIENTED MULTI-VIEW VIDEO COLOR CORRECTION

Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with multi-view video coding, a coding-oriented multi-view video color correction method is proposed. We first separate foreground and background in first Group Of Pictures （GOP） by using SKIP coding mode. Then by transferring means and standard deviations in backgrounds, color correction is performed for each frame in GOP, and multi-view video coding is performed and used to renew the backgrounds. Experimental results ances in color correction and multi-view video show the proposed method can obtain better performcoding.

Trifocal tensor based side information generation for multi-view distributed video code

Distributed video coding （DVC） is a new video coding approach based on Wyner-Ziv theorem. The novel uplink-friendly DVC, which offers low-complexity, low-power consuming, and low-cost video encoding, has aroused more and more research interests. In this paper a new method based on multiple view geometry is presented for spatial side information generation of uncalibrated video sensor network. Trifocal tensor encapsulates all the geometric relations among three views that are independent of scene structure; it can be computed from image correspondences alone without requiring knowledge of the motion or calibration. Simulation results show that trifocal tensor-based spatial side information improves the rate-distortion performance over motion compensation based interpolation side information by a maximum gap of around 2dB. Then fusion merges the different side information （temporal and spatial） in order to improve the quality of the final one. Simulation results show that the rate-distortion gains about 0.4 dB.

Benefiting from providing multi-dimensional view of peers in overlay of P2P streaming system

Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view including video data,peers' service capability and online stability based on locality sensitive hashing.MDOPS organizes all Live/VoD peers and the above multi-dimensional information in a one-dimensinal DHT,uses range resource information publish/search and introduces multiple load balancing methods.MDOPS maintains an additional candidate coordinating peer list with high qualified peers who own the video data the peer would possibly access currently and in future.This list could speed up the process of searching peers for data scheduling layer.Simulation experiment based on trace of real streaming system has testified that MDOPS can effectively improve the quality of search results and smooth load distribution among peers without increasing the cost of resource publish/search.

Classified-edge guided depth resampling for multi-view coding

A new depth resampling for multi-view coding is proposed in this paper.At first,the depth video is downsampled by median filtering before encoding.After decoding,the classified edges,including credible edge and probable edge from the aligned texture image and the depth image,are interpolated by the selected diagonal pair,whose intensity difference is the minimum among four diagonal pairs around edge pixel.According to different category of edge,the intensity difference is measured by either real depth or percentage depth without any parameter setting.Finally,the resampled depth video and the decoded full-resolution texture video are synthesized into virtual views for the performance evaluation.Experiments on the platform of multi-view high efficiency video coding(HEVC) demonstrate that the proposed method is superior to the contrastive methods in terms of visual quality and rate distortion(RD) performance.