Abstract
Consumer devices with stereo cameras have become popular because of their low-cost depth sensing capability. However, those systems usually suffer from low imaging quality and inaccurate depth acquisition under low-light conditions. To address the problem, we present a new stereo matching method with a color and monochrome camera pair. We focus on the fundamental trade-off that monochrome cameras have much better light-efficiency than color-filtered cameras. Our key ideas involve compensating for the radiometric difference between two crossspectral images and taking full advantage of complementary data. Consequently, our method produces both an accurate depth map and high-quality images, which are applicable for various depth-aware image processing. Our method is evaluated using various datasets and the performance of our depth estimation consistently outperforms state-of-the-art methods.
| Original language | English |
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| Title of host publication | Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 |
| Publisher | IEEE Computer Society |
| Pages | 4086-4094 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781467388504 |
| DOIs | |
| State | Published - 9 Dec 2016 |
| Event | 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 - Las Vegas, United States Duration: 26 Jun 2016 → 1 Jul 2016 |
Publication series
| Name | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
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| Volume | 2016-December |
| ISSN (Print) | 1063-6919 |
Conference
| Conference | 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 |
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| Country/Territory | United States |
| City | Las Vegas |
| Period | 26/06/16 → 1/07/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.