Depth-map generation for multi-view autostereoscopic 3-D displays based on the SIFT algorithm constrained by boundary

— A depth‐map estimation method, which converts two‐dimensional images into three‐dimensional (3‐D) images for multi‐view autostereoscopic 3‐D displays, is presented. The proposed method utilizes the Scale Invariant Feature Transform (SIFT) matching algorithm to create the sparse depth map. The imag...

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Bibliographic Details
Published in:Journal of the Society for Information Display 2010-07, Vol.18 (7), p.513-518
Main Authors: Zhang, Ying-Quan, Wang, Qiong-Hua, Wang, Ai-Hong, Li, Da-Hai
Format: Article
Language:English
Subjects:
Autostereoscopic display
depth map
SIFT matching algorithm
Sobel operator
zero-mean normalized cross-correlation
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Summary:— A depth‐map estimation method, which converts two‐dimensional images into three‐dimensional (3‐D) images for multi‐view autostereoscopic 3‐D displays, is presented. The proposed method utilizes the Scale Invariant Feature Transform (SIFT) matching algorithm to create the sparse depth map. The image boundaries are labeled by using the Sobel operator. A dense depth map is obtained by using the Zero‐Mean Normalized Cross‐Correlation (ZNCC) propagation matching method, which is constrained by the labeled boundaries. Finally, by using depth rendering, the parallax images are generated and synthesized into a stereoscopic image for multi‐view autostereoscopic 3‐D displays. Experimental results show that this scheme achieves good performances on both parallax image generation and multi‐view autostereoscopic 3‐D displays.
ISSN:1071-0922
1938-3657
DOI:10.1889/JSID18.7.513