Kemsaram, Narsimlu;
Das, Anweshan;
Dubbelman, Gijs;
(2020)
A Stereo Perception Framework for Autonomous Vehicles.
In:
2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring).
(pp. pp. 1-6).
IEEE: Antwerp, Belgium.
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Abstract
Stereo cameras are crucial sensors for self-driving vehicles as they are low-cost and can be used to estimate depth. It can be used for multiple purposes, such as object detection, depth estimation, semantic segmentation, etc. In this paper, we propose a stereo vision-based perception framework for autonomous vehicles. It uses three deep neural networks simultaneously to perform free-space detection, lane boundary detection, and object detection on image frames captured using the stereo camera. The depth of the detected objects from the vehicle is estimated from the disparity image computed using two stereo image frames from the stereo camera. The proposed stereo perception framework runs at 7.4 Hz on the Nvidia Drive PX 2 hardware platform, which further allows for its use in multi-sensor fusion for localization, mapping, and path planning by autonomous vehicle applications.
| Type: | Proceedings paper |
|---|---|
| Title: | A Stereo Perception Framework for Autonomous Vehicles |
| Event: | 91st Vehicular Technology Conference (VTC2020-Spring) |
| Dates: | 25 May 2020 - 28 May 2020 |
| ISBN-13: | 978-1-7281-5207-3 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/VTC2020-Spring48590.2020.9128899 |
| Publisher version: | http://dx.doi.org/10.1109/vtc2020-spring48590.2020... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Advanced driver assistance system, autonomous vehicle, deep neural network, depth estimation, free space detection, lane detection, object detection, stereo camera, stereo perception, stereo vision |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10187030 |
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