Accurate Depth Extraction Method for Multiple Light-Coding-Based Depth Cameras

Yu Pan

doi:10.1109/TMM.2016.2646179

Return

Accurate Depth Extraction Method for Multiple Light-Coding-Based Depth Cameras

2017-04-01

PRE

DOI：10.1109/TMM.2016.2646179

Original

Original request for help

Save

Abstract

Using multiple depth cameras can extend the field of view, which is beneficial to three-dimensional (3D) reconstruction. However, multiple active depth cameras would interfere with each other, which degrades the quality of depth images significantly. In this paper, we first present a depth extraction method based on sampling of the space at camera viewpoints to address the interference problem. Compared with the previous plane-sweeping method based on structured-light stereo and multiview stereo, depth images with less depth errors and better shape of objects are generated. Then, we analyze factors affecting depth accuracy for light-coding-based depth cameras and demonstrate the proposed depth extraction method also improves the accuracy of depth images by utilizing multiple projected patterns. Based on the analysis, subpixel-based matching (SPM) is finally applied to further improve the depth accuracy obtained by the depth extraction method. In the image matching process of our method, nearest neighbor interpolation is utilized to each projector's image plane to increase their resolution, which leads to the improved depth accuracy at subpixel level and avoids the drawbacks of changing parameters of light-coding-based depth cameras. Experimental results under simulated and real-world examples validate our analysis and show that the proposed method not only mitigates the impacts of interference effectively but also further improves the accuracy of depth images by using SPM.

Keywords:

Depth camera

depth extraction

depth accuracy

interference reduction

subpixel

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.