Automotive Applications for Embedded Vision
Vision products in automotive applications can make us better and safer drivers
Vision products in automotive applications can serve to enhance the driving experience by making us better and safer drivers through both driver and road monitoring.
Driver monitoring applications use computer vision to ensure that driver remains alert and awake while operating the vehicle. These systems can monitor head movement and body language for indications that the driver is drowsy, thus posing a threat to others on the road. They can also monitor for driver distraction behaviors such as texting, eating, etc., responding with a friendly reminder that encourages the driver to focus on the road instead.
In addition to monitoring activities occurring inside the vehicle, exterior applications such as lane departure warning systems can use video with lane detection algorithms to recognize the lane markings and road edges and estimate the position of the car within the lane. The driver can then be warned in cases of unintentional lane departure. Solutions exist to read roadside warning signs and to alert the driver if they are not heeded, as well as for collision mitigation, blind spot detection, park and reverse assist, self-parking vehicles and event-data recording.
Eventually, this technology will to lead cars with self-driving capability; Google, for example, is already testing prototypes. However many automotive industry experts believe that the goal of vision in vehicles is not so much to eliminate the driving experience but to just to make it safer, at least in the near term.
This blog post was originally published at Ambarella’s website. It is reprinted here with the permission of Ambarella. Both technologies are used for object detection in autonomous vehicles, but how do they compare? Autonomous vehicles typically deploy multiple sensor systems for environmental perception: LiDAR, radar, and camera modules being the most popular. These sensor systems
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