Exploiting and Refining Depth Distributions with Triangulation Light Curtains

Yaadhav Raaj ~ Siddharth Ancha ~ Robert Tamburo ~ David Held ~ Srinivasa G. Narasimhan

Carnegie Mellon University

Abstract

Active sensing through the use of Adaptive Depth Sensors is a nascent field, with potential in areas such as Advanced driver-assistance systems (ADAS). They do however require dynamically driving a laser / light-source to a specific location to capture information, with one such class of sensor being the Triangulation Light Curtains (LC). In this work, we introduce a novel approach that exploits prior depth distributions from RGB cameras to drive a Light Curtain's laser line to regions of uncertainty to get new measurements. These measurements are utilized such that depth uncertainty is reduced and errors get corrected recursively. We show real-world experiments that validate our approach in outdoor and driving settings, and demonstrate qualitative and quantitative improvements in depth RMSE when RGB cameras are used in tandem with a Light Curtain.

Publication

Exploiting and Refining Depth Distributions with Triangulation Light Curtains
Yaadhav Raaj ~ Siddharth Ancha ~ Robert Tamburo ~ David Held ~ Srinivasa G. Narasimhan
Computer Vision and Pattern Recognition (CVPR) 2021
[ Paper ]

Code

Code and dataset found here
[ Code ]

UPDATE: Code has been made private until we figure out the License. So Code coming soon!