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Stereo Matching with Color and Monochrome Cameras in Low-Light Conditions

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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.
Author(s)
Jeon, Hae-GonLee, Joon-YoungIm, SunghoonHa, HyowonKweon, In So
Issued Date
2016-06-29
Type
Conference Paper
DOI
10.1109/CVPR.2016.443
URI
https://scholar.gist.ac.kr/handle/local/20620
Publisher
IEEE Computer Society
Citation
29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, pp.4086 - 4094
ISSN
1063-6919
Conference Place
US
Las Vegas, NV, USA
Appears in Collections:
Department of AI Convergence > 2. Conference Papers
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