Virtual View Rendering Based on Self-adaptive Block Matching Disparity Estimation

2012 ◽  
Author(s):  
Shiping Zhu ◽  
Yang Yu
Keyword(s):  
Block Matching ◽  
Disparity Estimation ◽  
Virtual View ◽  
Virtual View Rendering ◽  
Self Adaptive

Depth Map Intra Coding Based on Virtual View Rendering Distortion Estimation

2011 ◽  
Vol 33 (11) ◽  
pp. 2541-2546 ◽  
Author(s):  
Qiu-wen Zhang ◽  
Ping An ◽  
Yan Zhang ◽  
Zhao-yang Zhang
Keyword(s):  
Depth Map ◽  
Intra Coding ◽  
Virtual View ◽  
Distortion Estimation ◽  
Virtual View Rendering

scholarly journals A New Virtual View Rendering Method based on Depth Map for 3DTV3DTV; virtual view rendering; depth; false contour; holes filling; image restoration

2011 ◽  
Vol 15 ◽  
pp. 1115-1119
Author(s):  
Linwei Zhu ◽  
Mei Yu ◽  
Gangyi Jiang ◽  
Xiangying Mao ◽  
Songyin Fu ◽  
...  
Keyword(s):  
Image Restoration ◽  
Depth Map ◽  
Virtual View ◽  
Virtual View Rendering

Virtual View Rendering Based on Depth Map Preprocessing and Image Inpainting

2019 ◽  
Vol 31 (8) ◽  
pp. 1278
Author(s):  
Haitao Liang ◽  
Xiaodong Chen ◽  
Huaiyuan Xu ◽  
Siyu Ren ◽  
Yi Wang ◽  
...  
Keyword(s):  
Image Inpainting ◽  
Depth Map ◽  
Virtual View ◽  
Virtual View Rendering

scholarly journals Edge-aided virtual view rendering for multiview video plus depth

2013 ◽  
Author(s):  
Suryanarayana M. Muddala ◽  
Mårten Sjöström ◽  
Roger Olsson ◽  
Sylvain Tourancheau
Keyword(s):  
Virtual View ◽  
Multiview Video ◽  
Virtual View Rendering

Motion Estimation Based on Adaptive Kalman Filter and Its Application in Video Coding

2011 ◽  
Vol 58-60 ◽  
pp. 2546-2551
Author(s):  
Cheng Guo ◽  
Hao Qian Wang
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Moving Average ◽  
Arma Model ◽  
Block Matching ◽  
Disparity Estimation ◽  
Autoregressive Moving Average ◽  
Moving Average Process ◽  
Adaptive Kalman Filter ◽  
Filtering Algorithm

Most of the traditional block-matching algorithms for motion estimation (ME) can only yield local optimal motion vectors (MVs). In this paper, the autoregressive moving average process (ARMA) model is selected to formulate the correlation of neighboring blocks in a frame, and the adaptive Kalman filtering algorithm is applied to refine the MVs. The horizontal and vertical ARMA models are constructed to utilize the filtering algorithm twice to get a better performance. Our method can also be extended to realize disparity estimation (DE) in order to apply it in a multi-view video coding (MVC) system. The experiment results show the effectiveness of our method to improve the accuracy of conventional fast block matching algorithms.

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