U-V-disparity: an efficient algorithm for stereovision based scene analysis

Reliable understanding of the 3D driving environment is vital for obstacle detection and adaptive cruise control (ACC) applications. Laser or millimeter wave radars have shown good performance in measuring relative speed and distance in a highway driving environment. However the accuracy of these sy...

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Bibliographic Details
Main Authors: Hu, Z., Uchimura, K.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive control
Image analysis
Laser applications
Laser radar
Millimeter wave measurements
Millimeter wave radar
Programmable control
Radar detection
Radar measurements
Roads
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Summary:Reliable understanding of the 3D driving environment is vital for obstacle detection and adaptive cruise control (ACC) applications. Laser or millimeter wave radars have shown good performance in measuring relative speed and distance in a highway driving environment. However the accuracy of these systems decreases in an urban traffic environment as more confusion occurs due to factors such as parked vehicles, guardrails, poles and motorcycles. A stereovision based sensing system provides an effective supplement to radar-based road scene analysis with its much wider field of view and more accurate lateral information. This paper presents an efficient solution using a stereovision based road scene analysis algorithm, which employs the "U-V-disparity" concept. This concept is used to classify a 3D road scene into relative surface planes and characterize the features of road pavement surfaces, roadside structures and obstacles. Real-time implementation of the disparity map calculation and the "U-V-disparity" classification is also presented.
ISSN:1931-0587
2642-7214
DOI:10.1109/IVS.2005.1505076