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Detecting Darting Out Pedestrians With Occlusion Aware Sensor Fusion of Radar and Stereo Camera

Andras Palffy, Julian F. P. Kooij, Dariu M. Gavrila

2022IEEE Transactions on Intelligent Vehicles34 citationsDOI

Abstract

Early and accurate detection of crossing pedestrians is crucial in automated driving in order to perform timely emergency manoeuvres. However, this is a difficult task in urban scenarios where pedestrians are often occluded (not visible) behind objects, e.g., other parked vehicles. We propose an occlusion aware fusion of stereo camera and radar sensors to address scenarios with crossing pedestrians behind such parked vehicles. Our proposed method adapts both the expected rate and properties of detections in different areas according to the visibility of the sensors. In our experiments on a real-world dataset, we show that the proposed occlusion aware fusion of radar and stereo camera detects the crossing pedestrians on average 0.26 seconds earlier than using the camera alone, and 0.15 seconds earlier than fusing the sensors without occlusion information. Our dataset containing 501 relevant recordings of pedestrians behind vehicles will be publicly available on our website for non-commercial, scientific use.

Topics & Concepts

Computer visionArtificial intelligenceComputer scienceVisibilityTask (project management)FusionRadarStereo cameraSensor fusionGeographyEngineeringTelecommunicationsLinguisticsSystems engineeringPhilosophyMeteorologyAdvanced Neural Network ApplicationsAutonomous Vehicle Technology and SafetyVideo Surveillance and Tracking Methods
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