Dual Exposure Stereo for Extended Dynamic Range 3D Imaging

Fuente: arXiv
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Hauptverfasser: Choi, Juhyung, Kim, Jinnyeong, Choi, Seokjun, Lee, Jinwoo, Brucker, Samuel, Bijelic, Mario, Heide, Felix, Baek, Seung-Hwan
Format: Preprint
Veröffentlicht: 2024
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author Choi, Juhyung
Kim, Jinnyeong
Choi, Seokjun
Lee, Jinwoo
Brucker, Samuel
Bijelic, Mario
Heide, Felix
Baek, Seung-Hwan
author_facet Choi, Juhyung
Kim, Jinnyeong
Choi, Seokjun
Lee, Jinwoo
Brucker, Samuel
Bijelic, Mario
Heide, Felix
Baek, Seung-Hwan
contents Achieving robust stereo 3D imaging under diverse illumination conditions is an important however challenging task, due to the limited dynamic ranges (DRs) of cameras, which are significantly smaller than real world DR. As a result, the accuracy of existing stereo depth estimation methods is often compromised by under- or over-exposed images. Here, we introduce dual-exposure stereo for extended dynamic range 3D imaging. We develop automatic dual-exposure control method that adjusts the dual exposures, diverging them when the scene DR exceeds the camera DR, thereby providing information about broader DR. From the captured dual-exposure stereo images, we estimate depth using motion-aware dual-exposure stereo network. To validate our method, we develop a robot-vision system, collect stereo video datasets, and generate a synthetic dataset. Our method outperforms other exposure control methods.
format Preprint
id arxiv_https___arxiv_org_abs_2412_02351
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Dual Exposure Stereo for Extended Dynamic Range 3D Imaging
Choi, Juhyung
Kim, Jinnyeong
Choi, Seokjun
Lee, Jinwoo
Brucker, Samuel
Bijelic, Mario
Heide, Felix
Baek, Seung-Hwan
Computer Vision and Pattern Recognition
Achieving robust stereo 3D imaging under diverse illumination conditions is an important however challenging task, due to the limited dynamic ranges (DRs) of cameras, which are significantly smaller than real world DR. As a result, the accuracy of existing stereo depth estimation methods is often compromised by under- or over-exposed images. Here, we introduce dual-exposure stereo for extended dynamic range 3D imaging. We develop automatic dual-exposure control method that adjusts the dual exposures, diverging them when the scene DR exceeds the camera DR, thereby providing information about broader DR. From the captured dual-exposure stereo images, we estimate depth using motion-aware dual-exposure stereo network. To validate our method, we develop a robot-vision system, collect stereo video datasets, and generate a synthetic dataset. Our method outperforms other exposure control methods.
title Dual Exposure Stereo for Extended Dynamic Range 3D Imaging
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2412.02351