Real-time pedestrian detection using radar-camera fusion and clustering

Kirsnaragavan Arudpiragasam; Taraka Rama Krishna Kanth Kannuri; Klaus Schwarz; Michael Hartmann; Reiner Creutzburg

doi:10.1117/12.2664270

15 June 2023 Real-time pedestrian detection using radar-camera fusion and clustering

Kirsnaragavan Arudpiragasam, Taraka Rama Krishna Kanth Kannuri, Klaus Schwarz, Michael Hartmann, Reiner Creutzburg

Proceedings Volume 12526, Multimodal Image Exploitation and Learning 2023 ; 125260E (2023) https://doi.org/10.1117/12.2664270
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

The design and development of autonomous vehicles ensure to move safely on roads while focusing on pedestrian detection systems has brought convention so that pedestrians can be detected quickly and precisely. Moreover, the researchers have mentioned that pedestrian skin detection has proven to be a tough challenge since the color of the skin can vary in appearance due to various factors such as weather conditions, sun lighting, occlusion, race, etc. Our proposed methodology, the radar-camera fusion technique, is used to predict the obstacle in any scenario. A convolution neural network extracts pedestrian features from RGB images and radar data. Also, we have introduced data preparation and feature extraction. We feature mapping to get more detection accuracy and clustering to find the similarities between features that will attain darker skin pedestrian details.

Conference Presentation

Citation Download Citation

Kirsnaragavan Arudpiragasam, Taraka Rama Krishna Kanth Kannuri, Klaus Schwarz, Michael Hartmann, and Reiner Creutzburg "Real-time pedestrian detection using radar-camera fusion and clustering", Proc. SPIE 12526, Multimodal Image Exploitation and Learning 2023 , 125260E (15 June 2023); https://doi.org/10.1117/12.2664270

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