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[bibtex]@InProceedings{Raaj_2021_CVPR, author = {Raaj, Yaadhav and Ancha, Siddharth and Tamburo, Robert and Held, David and Narasimhan, Srinivasa G.}, title = {Exploiting & Refining Depth Distributions With Triangulation Light Curtains}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2021}, pages = {7434-7442} }
Exploiting & Refining Depth Distributions With Triangulation Light Curtains
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.
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