English

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

Neural and Evolutionary Computing 2023-07-26 v1 Computer Vision and Pattern Recognition

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.

Keywords

Cite

@article{arxiv.2307.13600,
  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},
  journal= {arXiv preprint arXiv:2307.13600},
  year   = {2023}
}

Comments

The Paper is accepted in 25th Irish Machine Vision and Image Processing Conference (IMVIP23)

R2 v1 2026-06-28T11:39:48.872Z