Decisive Data using Multi-Modality Optical Sensors for Advanced Vehicular Systems

Muhammad Ali Farooq, Waseem Shariff, Mehdi Sefidgar Dilmaghani, Wang Yao, Moazam Soomro +1 more
7/25/2023
cs.NEcs.CV

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Abstract

Optical sensors have played a pivotal role in acquiring real world data for critical applications. This data, when integrated with advanced machine learning algorithms provides meaningful information thus enhancing human vision. This paper focuses on various optical technologies for design and development of state-of-the-art out-cabin forward vision systems and in-cabin driver monitoring systems. The focused optical sensors include Longwave Thermal Imaging (LWIR) cameras, Near Infrared (NIR), Neuromorphic/ event cameras, Visible CMOS cameras and Depth cameras. Further the paper discusses different potential applications which can be employed using the unique strengths of each these optical modalities in real time environment.

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@article{farooq2023decisive,
  title  = {Decisive Data using Multi-Modality Optical Sensors for Advanced Vehicular Systems},
  author = {Muhammad Ali Farooq and Waseem Shariff and Mehdi Sefidgar Dilmaghani and Wang Yao and Moazam Soomro and Peter Corcoran},
  year   = {2023},
  eprint = {2307.13600},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.13600v1}
}

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