2D to 3D Depth Map Prediction Based on Image Segmentation

QIAN Zhixuan; WANG Chensheng; YANG Guang; LI Yangguang; JING Xueliang; LI Yanjiang

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2D to 3D Depth Map Prediction Based on Image Segmentation

QIAN Zhixuan 1,WANG Chensheng 2 *,YANG Guang 2,LI Yangguang 2,JING Xueliang 2,LI Yanjiang 2

1.Beijing University of Posts and Telecommunications,Automation school,Bei jing 100876;Beijing University of Posts and Telecommunications,Automation school,Bei jing 100876;Beijing University of Posts and Telecommunications,Automation school,Bei jing 100876;Beijing University of Posts and Telecommunications,Automation school,Bei jing 100876;Beijing University of Posts and Telecommunications,Automation school,Bei jing 100876;Beijing University of Posts and Telecommunications,Automation school,Bei jing 100876

*Correspondence author

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Funding: none

Opened online:30 April 2020

Accepted by: none

Citation: QIAN Zhixuan,WANG Chensheng,YANG Guang.2D to 3D Depth Map Prediction Based on Image Segmentation[OL]. [30 April 2020] http://en.paper.edu.cn/en_releasepaper/content/4751786

This paper proposes an algorithm to convert 2D video of road video to 3D video.In this kind of video, the foreground is the most concerned part, and accurately extracting the foreground object from the background is the key to get the depth map. In this paper, a graph cutting algorithm based on machine learning is used to obtain the foreground, and the background depth model is constructed according to the scene structure to obtain the background depth map. Based on the background depth map, the depth of the foreground object is assigned according to the distance relationship between the foreground and the lens. Then, the background depth map and foreground depth map are combined to obtain a complete depth map.

Keywords:depth map prediction;2D to 3D;image segmentation

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