期刊
IEEE ROBOTICS AND AUTOMATION LETTERS
卷 7, 期 2, 页码 1040-1047出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2021.3137520
关键词
Computer vision for automation; SLAM
类别
This research develops an image processing technique using burst photography to improve the robustness and accuracy of 3D reconstruction in low light conditions. The method shows improved performance in challenging light-constrained scenes and has potential applications for robots operating in environments with limited light.
Images captured under extremely low light conditions are noise-limited, which can cause existing robotic vision algorithms to fail. In this letter we develop an image processing technique for aiding 3D reconstruction from images acquired in low light conditions. Our technique, based on burst photography, uses direct methods for image registration within bursts of short exposure time images to improve the robustness and accuracy of feature-based structure-from-motion (SfM). We demonstrate improved SfM performance in challenging light-constrained scenes, including quantitative evaluations that show improved feature performance and camera pose estimates. Additionally, we show that our method converges more frequently to correct reconstructions than the state-of-the-art. Our method is a significant step towards allowing robots to operate in low light conditions, with potential applications to robots operating in environments such as underground mines and night time operation.
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