Decisive Data using Multi-Modality Optical Sensors for Advanced Vehicular Systems
This work addresses the problem of improving safety and functionality in autonomous and assisted driving systems for automotive applications, but it appears incremental as it focuses on discussing existing sensor technologies and their potential applications without presenting new methods or results.
The paper tackles the integration of multiple optical sensor technologies, including LWIR, NIR, neuromorphic, visible, and depth cameras, for advanced vehicular systems such as out-cabin forward vision and in-cabin driver monitoring, aiming to enhance human vision through machine learning algorithms.
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.