Real-Time Depth Refinement for Specular Objects
Abstract
The introduction of consumer RGB-D scanners set off a major boost in 3D computer vision research. Yet, the precision of existing depth scanners is not accurate enough to recover fine details of a scanned object. While modern shading based depth refinement methods have been proven to work well with Lambertian objects, they break down in the presence of specularities. We present a novel shape from shading framework that addresses this issue and enhances both diffuse and specular objects' depth profiles. We take advantage of the built-in monochromatic IR projector and IR images of the RGB-D scanners and present a lighting model that accounts for the specular regions in the input image. Using this model, we reconstruct the depth map in real-time. Both quantitative tests and visual evaluations prove that the proposed method produces state of the art depth reconstruction results.
Cite
Text
Or-El et al. "Real-Time Depth Refinement for Specular Objects." Conference on Computer Vision and Pattern Recognition, 2016. doi:10.1109/CVPR.2016.474Markdown
[Or-El et al. "Real-Time Depth Refinement for Specular Objects." Conference on Computer Vision and Pattern Recognition, 2016.](https://mlanthology.org/cvpr/2016/orel2016cvpr-realtime/) doi:10.1109/CVPR.2016.474BibTeX
@inproceedings{orel2016cvpr-realtime,
title = {{Real-Time Depth Refinement for Specular Objects}},
author = {Or-El, Roy and Hershkovitz, Rom and Wetzler, Aaron and Rosman, Guy and Bruckstein, Alfred M. and Kimmel, Ron},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2016},
doi = {10.1109/CVPR.2016.474},
url = {https://mlanthology.org/cvpr/2016/orel2016cvpr-realtime/}
}