DocumentCode :
2657551
Title :
A New Improved Depth Estimation Algorithm Based on Gradient Feature for Preserving Consistency among Views
Author :
Wang XiangQian ; Shen, Liquan ; Jiang, Yizhong ; Zhang, Zhaoyang
Author_Institution :
Key Lab. of Adv. Display & Syst. Applic. of the Minist. of Educ., Shanghai Univ., Shanghai, China
fYear :
2011
fDate :
4-6 Nov. 2011
Firstpage :
37
Lastpage :
40
Abstract :
In this paper we introduce a more reliable depth estimation algorithm, which is effective in improving the depth maps. With the commercial development of three-dimensional television (3DTV), the corresponding three-dimensional productions are becoming more popular. Especially, the depth estimation is one of the key technologies of multi-view video (MVV) and free viewpoint video (FVV) systems, but how to get accurate depth information is becoming the key issue. Based on the existing depth estimation reference algorithm (DERS), the proposed algorithm takes the improvements of the data term of the global algorithm. As experiment results show, our method not only improves the objective quality of synthesized virtual images in terms of PSNR, but also makes the subjective visual effect better.
Keywords :
feature extraction; three-dimensional television; video signal processing; commercial development; depth estimation reference algorithm; free viewpoint video system; gradient feature; improved depth estimation algorithm; multiview video; preserving consistency; reliable depth estimation algorithm; synthesized virtual image; three-dimensional production; three-dimensional television; Brightness; Estimation; Image color analysis; Minimization; Stereo vision; Three dimensional displays; Video sequences; 3DTV; depth estimation; gradient feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Information Networking and Security (MINES), 2011 Third International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-1795-6
Type :
conf
DOI :
10.1109/MINES.2011.125
Filename :
6103717
Link To Document :
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