High-Performance Long Range Obstacle Detection Using Stereo Vision
2015 (English)In: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), IEEE , 2015, 1308-1313 p.Conference paper (Refereed)Text
Reliable detection of obstacles at long range is crucial for the timely response to hazards by fast-moving safety-critical platforms like autonomous cars. We present a novel method for the joint detection and localization of distant obstacles using a stereo vision system on a moving platform. The approach is applicable to both static and moving obstacles and pushes the limits of detection performance as well as localization accuracy. The proposed detection algorithm is based on sound statistical tests using local geometric criteria which implicitly consider non-flat ground surfaces. To achieve maximum performance, it operates directly on image data instead of precomputed stereo disparity maps. A careful experimental evaluation on several datasets shows excellent detection performance and localization accuracy up to very large distances, even for small obstacles. We demonstrate a parallel implementation of the proposed system on a GPU that executes at real-time speeds.
Place, publisher, year, edition, pages
IEEE , 2015. 1308-1313 p.
, IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:liu:diva-127068DOI: 10.1109/IROS.2015.7353537ISI: 000371885401068ISBN: 978-1-4799-9994-1OAI: oai:DiVA.org:liu-127068DiVA: diva2:919357
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)