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13 June 2022 Multimodal realtime pedestrian detection using radar-camera fusion with clustering
Kirsnaragavan Arudpiragasam Kannuri, Taraka Rama Krishna Kanth, Klaus Schwarz, Michael Hartmann, Reiner M. Creutzburg
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Proceedings Volume PC12100, Multimodal Image Exploitation and Learning 2022; PC1210005 (2022) https://doi.org/10.1117/12.2619013
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States
Abstract
Autonomous vehicles design and development can move safely on roads while sensing the environment to focus on pedestrian detection systems so that people can be detected as quickly and accurately as possible. First, however, it is critical to examine the pedestrians themselves and their color, which benefits from being insensitive to changes in scale and partial occlusion. Moreover, human skin detection has proven to be a tough challenge since skin color can vary considerably in appearance due to various factors such as lighting, race, and imaging circumstances. Unfortunately, human skin detection has not been thoroughly investigated in this circumstance, and it appears that many studies do not address this systematically when it comes to pedestrian detection systems for autonomous cars. To overcome this issue, we are using a Radar-Camera fusion technique to predict obstacles in various daylight situations.
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Kirsnaragavan Arudpiragasam Kannuri, Taraka Rama Krishna Kanth, Klaus Schwarz, Michael Hartmann, and Reiner M. Creutzburg "Multimodal realtime pedestrian detection using radar-camera fusion with clustering", Proc. SPIE PC12100, Multimodal Image Exploitation and Learning 2022, PC1210005 (13 June 2022); https://doi.org/10.1117/12.2619013
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KEYWORDS
Skin
Unmanned vehicles
Convolutional neural networks
Environmental sensing
Light sources and illumination
Roads
Sensing systems
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