Learning-Deep-Learning

Vehicle Centric Monocular Velocity: End-to-end Learning for Inter-Vehicle Distance and Relative Velocity Estimation in ADAS with a Monocular Camera

July 2020

tl;dr: Distance and velocity estimation from monocular video.

Overall impression

Achieves better performance and is more end to end than monocular_velocity. It uses optical flow and RoIAligned features to regress velocity and distance. It does not use off-the-shelf depth estimator as in monocular_velocity.

3D velocity estimation can be seen as the prediction of sparse scene flow. This is to be compared to the 2d offset prediction in CenterTrack, which can be seen as a sparse optical flow. Scene flow = optical flow + depth.

SOTA velocity estimation is about 0.48 m/s.

Key ideas

Technical details

Notes