In-cabin sensing using computer vision refers to the application of computer vision techniques to monitor and analyze the interior of a vehicle's cabin. By using cameras and computer vision algorithms, in-cabin sensing systems can detect and interpret various information about the occupants and their activities inside the vehicle.
In-cabin monitoring system (IMS) for safety, security, surveillance, and monitoring, including privacy concerns for personal and shared autonomous vehicles (AVs). It consists of a set of monitoring cameras and an onboard device (OBD) equipped with artificial intelligence (AI).
In-cabin sensing using computer vision refers to the application of computer vision techniques to monitor and analyze the interior of a vehicle's cabin. By using cameras and computer vision algorithms, in-cabin sensing systems can detect and interpret various information about the occupants and their activities inside the vehicle.
In-cabin monitoring system (IMS) for safety, security, surveillance, and monitoring, including privacy concerns for personal and shared autonomous vehicles (AVs). It consists of a set of monitoring cameras and an onboard device (OBD) equipped with artificial intelligence (AI).
Monitoring and surveillance are essential in highly automated driving. Broader categorizations are related to the safety, security, and privacy of the occupants.
Check if the driver is focused on the road, mirrors, or other important visual cues. It can also help detect driver distraction if the gaze is consistently directed away from the driving environment.
To capture the driver's face and track facial features in real time. Facial recognition algorithms analyze facial landmarks such as eyes, eyebrows, mouth, and head position to understand the driver's state.
Detect the heart-rate of the driver which can help detect driver fatigue, stress, or health issues.
Detects signs of driver fatigue, distraction, or impairment
Detect users age and gender