In addition to the ToF image sensor still has great application prospects in consumer electronics, its potential in the Internet of Things field also has the potential to be tapped. Judging from the market share of ToF sensors, following the smartphone and tablet markets are building inspection, smart home, automotive central control, and drones.
With such a wide range of application scenarios, it benefits from the advantages of the ToF image sensor compared to structured light and binocular RGB: the depth information of the object is quickly calculated in real time, and the depth calculation is not affected by the grayscale characteristics of the object surface. The accuracy will not change with the change of distance, and it can basically guarantee the accuracy of centimeter level, especially suitable for some large-scale distance changes and high-speed applications.
In addition, it is an active light source beam, so under the condition that the light source does not harm the human eye, the theoretical maximum detection distance of the ToF sensor can reach 100m, and the light source can be adjusted flexibly to switch the required distance. In addition, the anti-interference ability and cost advantages of ToF sensors are also obvious.
Specifically, in the Internet of Things scenarios, smart home, smart security, smart retail, people flow monitoring, ToF sensors are used to identify and track the human body, not only the current face recognition mode, but the recognition accuracy can be improved through depth information; In the field of autonomous driving/in-vehicle perception, ToF sensors can also become important components for in-vehicle lidar, in-vehicle body recognition, and in-vehicle gesture recognition. At present, many companies have implanted ToF sensors into AGVs and robot arms for precise navigation and real-time obstacle avoidance.
In general, for 2D recognition technology that did not have depth information before, ToF sensors can greatly increase the recognition dimension and improve the security, comprehensiveness and accuracy of recognition.
