Depth Map Estimation and Colorization of Anaglyph Images Using Local Color Prior and Reverse Intensity Distribution
Author(s)Williem; Park, In Kyu; Raskar, Ramesh
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In this paper, we present a joint iterative anaglyph stereo matching and colorization framework for obtaining a set of disparity maps and colorized images. Conventional stereo matching algorithms fail when addressing anaglyph images that do not have similar intensities on their two respective view images. To resolve this problem, we propose two novel data costs using local color prior and reverse intensity distribution factor for obtaining accurate depth maps. To colorize an anaglyph image, each pixel in one view is warped to another view using the obtained disparity values of non-occluded regions. A colorization algorithm using optimization is then employed with additional constraint to colorize the remaining occluded regions. Experimental results confirm that the proposed unified framework is robust and produces accurate depth maps and colorized stereo images.
DepartmentMassachusetts Institute of Technology. Media Laboratory; Program in Media Arts and Sciences (Massachusetts Institute of Technology)
2015 IEEE International Conference on Computer Vision (ICCV)
Institute of Electrical and Electronics Engineers (IEEE)
Williem, Ramesh Raskar, and In Kyu Park. “Depth Map Estimation and Colorization of Anaglyph Images Using Local Color Prior and Reverse Intensity Distribution.” 2015 IEEE International Conference on Computer Vision (ICCV) (December 2015).
Author's final manuscript