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http://dx.doi.org/10.7236/JIWIT.2011.11.3.129

2D to 3D Conversion Using The Machine Learning-Based Segmentation And Optical Flow  

Lee, Sang-Hak (SK c&c 3D 솔루션 사업팀)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.11, no.3, 2011 , pp. 129-135 More about this Journal
Abstract
In this paper, we propose the algorithm using optical flow and machine learning-based segmentation for the 3D conversion of 2D video. For the segmentation allowing the successful 3D conversion, we design a new energy function, where color/texture features are included through machine learning method and the optical flow is also introduced in order to focus on the regions with the motion. The depth map are then calculated according to the optical flow of segmented regions, and left/right images for the 3D conversion are produced. Experiment on various video shows that the proposed method yields the reliable segmentation result and depth map for the 3D conversion of 2D video.
Keywords
2D/3D Conversion; Optical Flow; Segmentation; Depth Map; Machine Learning;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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