Single-shot monocular RGB-D imaging using uneven double refraction

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Cameras that capture color and depth information have become an essential imaging modality for applications in robotics, autonomous driving, virtual, and augmented reality. Existing RGB-D cameras rely on multiple sensors or active illumination with specialized sensors. In this work, we propose a method for monocular single-shot RGB-D imaging. Instead of learning depth from single-image depth cues, we revisit double-refraction imaging using a birefractive medium, measuring depth as the displacement of differently refracted images superimposed in a single capture. However, existing double-refraction methods are orders of magnitudes too slow to be used in real-time applications, e.g., in robotics, and provide only inaccurate depth due to correspondence ambiguity in double reflection. We resolve this ambiguity optically by leveraging the orthogonality of the two linearly polarized rays in double refraction - introducing uneven double refraction by adding a linear polarizer to the birefractive medium. Doing so makes it possible to develop a real-time method for reconstructing sparse depth and color simultaneously in real-time. We validate the proposed method, both synthetically and experimentally, and demonstrate 3D object detection and photographic applications.
Publisher
IEEE Computer Society
Issue Date
2020-06-16
Language
English
Citation

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020, pp.2462 - 2471

DOI
10.1109/CVPR42600.2020.00254
URI
http://hdl.handle.net/10203/277143
Appears in Collection
CS-Conference Papers(학술회의논문)
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