BuFF: Burst Feature Finder for Light-Constrained 3D Reconstruction

• Published in: IEEE robotics and automation letters Vol. 8; no. 12; pp. 8438 - 8445
• Main Authors: Ravendran, Ahalya, Bryson, Mitch, Dansereau, Donald G.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-12-2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cameras; Computer vision for automation; Feature detection; Feature extraction; Image reconstruction; Imaging techniques; Pose estimation; Robot vision systems; Robotics; Robots; Signal to noise ratio; SLAM; Three-dimensional displays
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2023.3329355

Robots operating in low-light conditions with conventional cameras face significant challenges due to the low signal-to-noise ratio in the images. Previous work has demonstrated the use of burst-imaging techniques to partially overcome this issue. This study proposes a novel feature finder that enhances vision-based reconstruction under extremely low-light conditions. The approach locates features with well-defined scale and apparent motion within each burst by jointly searching in a scale-slope space. We demonstrate improved performance in feature detection, camera pose estimation and reconstruction compared to state-of-the-art feature extractors on conventional and burst-merged images. This work opens avenues for robotic applications where low-light conditions often pose difficulties such as disaster recovery and drone delivery at night.