Decisive Data using Multi-Modality Optical Sensors for Advanced
  Vehicular Systems
Muhammad Ali Farooq Waseem Shariff Mehdi Sefidgar Dilmaghani Wang Yao Moazam Soomro Peter Corcoran
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.