Depth sensing beyond lidar range

Kai Zhang, Jiaxin Xie, Noah Snavely, Qifeng Chen

Research output: Contribution to journalConference article published in journalpeer-review

Abstract

Depth sensing is a critical component of autonomous driving technologies, but today's LiDAR- or stereo camera-based solutions have limited range. We seek to increase the maximum range of self-driving vehicles' depth perception modules for the sake of better safety. To that end, we propose a novel three-camera system that utilizes small field of view cameras. Our system, along with our novel algorithm for computing metric depth, does not require full pre-calibration and can output dense depth maps with practically acceptable accuracy for scenes and objects at long distances not well covered by most commercial LiDARs.

Original languageEnglish
Article number9156562
Pages (from-to)1689-1697
Number of pages9
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
DOIs
Publication statusPublished - 2020
Event2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020 - Virtual, Online, United States
Duration: 14 Jun 202019 Jun 2020

Bibliographical note

Publisher Copyright:
© 2020 IEEE Computer Society. All rights reserved.

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