Using virtual environment for autonomous vehicle algorithm validation

Aleksandrs Levinskis

doi:10.1117/12.2310175

13 April 2018 Using virtual environment for autonomous vehicle algorithm validation

Aleksandrs Levinskis

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106961R (2018) https://doi.org/10.1117/12.2310175
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

Abstract

This paper describes possible use of modern game engine for validating and proving the concept of algorithm design. As the result simple visual odometry algorithm will be provided to show the concept and go over all workflow stages. Some of stages will involve using of Kalman filter in such a way that it will estimate optical flow velocity as well as position of moving camera located at vehicle body. In particular Unreal Engine 4 game engine will be used for generating optical flow patterns and ground truth path. For optical flow determination Horn and Schunck method will be applied. As the result, it will be shown that such method can estimate position of the camera attached to vehicle with certain displacement error respect to ground truth depending on optical flow pattern. For displacement rate RMS error is calculating between estimated and actual position.

Citation Download Citation

Aleksandrs Levinskis "Using virtual environment for autonomous vehicle algorithm validation", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106961R (13 April 2018); https://doi.org/10.1117/12.2310175

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available