Robust Monocular Visual-Inertial Depth Completion for Embedded Systems
Nathaniel Merrill Patrick Geneva Guoquan Huang Nathaniel Merrill Patrick Geneva Guoquan Huang
In this work we augment our prior state-of-the-art visual-inertial odometry (VIO) system, OpenVINS [1], to produce accurate dense depth by filling in sparse depth estimates (depth completion) from VIO with image guidance – all while focusing on enabling real-time performance of the full VIO+depth system on embedded devices. We show that noisy depth values with varying sparsity produced from a VIO ...