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

Hoffmann M, Braun S, Sura O, Stelzig M, Schüßler C, Graichen K, Vossiek M (2023)

Publication Type: Conference contribution

Publication year: 2023

Publisher: Institute of Electrical and Electronics Engineers Inc.

Conference Proceedings Title: Proceedings of the IEEE Radar Conference

Event location: Sydney, NSW

ISBN: 9781665482783

DOI: 10.1109/RADAR54928.2023.10371183

Abstract

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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How to cite

APA:

Hoffmann, M., Braun, S., Sura, O., Stelzig, M., Schüßler, C., Graichen, K., & Vossiek, M. (2023). Concept for an Automatic Annotation of Automotive Radar Data Using AI-segmented Aerial Camera Images. In Proceedings of the IEEE Radar Conference. Sydney, NSW, AU: Institute of Electrical and Electronics Engineers Inc..

MLA:

Hoffmann, Marcel, et al. "Concept for an Automatic Annotation of Automotive Radar Data Using AI-segmented Aerial Camera Images." Proceedings of the 2023 IEEE International Radar Conference, RADAR 2023, Sydney, NSW Institute of Electrical and Electronics Engineers Inc., 2023.

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