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Concept for an Automatic Annotation of Automotive Radar Data Using AI-segmented Aerial Camera Images

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arxiv 2309.00268 v1 pith:XXFBNRTL submitted 2023-09-01 eess.SP

Marcel Hoffmann , Sandro Braun , Oliver Sura , Michael Stelzig , Christian Schü{ss}ler , Knut Graichen , Martin Vossiek This is my paper · ORCID
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keywords radarcameradataimagesaerialai-segmentedautomaticallyautomotive
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This paper presents an approach to automatically annotate automotive radar data with AI-segmented aerial camera images. For this, the images of an unmanned aerial vehicle (UAV) above a radar vehicle are panoptically segmented and mapped in the ground plane onto the radar images. The detected instances and segments in the camera image can then be applied directly as labels for the radar data. Owing to the advantageous bird's eye position, the UAV camera does not suffer from optical occlusion and is capable of creating annotations within the complete field of view of the radar. The effectiveness and scalability are demonstrated in measurements, where 589 pedestrians in the radar data were automatically labeled within 2 minutes.

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