Cloudwalk in vivo detection algorithm covers many categories, e.g. active in vivo detection, silent in vivo detection, infrared in vivo detection, structured light/TOF in vivo detection and 3D in vivo detection.
The Cloudwalk in vivo detection camera based on the original core algorithm developed by Cloudwalk is the first product of its kind in China to pass the national standard test, with the in vivo detection performance reaching the highest security level (enhanced level) in the financial payment standard. Supporting infrared monocular/binocular camera for in vivo detection, the Cloudwalk in vivo detection camera achieves in live detection and face recognition algorithms on low computing platform with embedded module featuring fast startup and low power consumption as well as simplified and optimized neural network.
Cloudwalk launched its first 3D structured light face recognition technology in February 2018. Compared with the previous 2D face recognition and infrared in vivo detection technology, the 3D structured light technology has made a great leap forward in security, recognition accuracy and recognition speed. It achieves an accuracy of above 99% at an error rate of 1/1000000 and reduces the recognition time from 1-2 seconds to 1-2 milliseconds, so as to effectively defend against fraudulent means like masks and videos.
Background and challenges
-
As a new touchpoint for interacting with consumers, smart containers enhance the retail experience through AI technology -
Enterprise operations face high cost pressure challenges such as manpower and rent -
With the continuous maturity of technology, the overall cost of the entire machine has significantly decreased. In addition, the products that can be sold in smart containers are not limited by packaging, materials, and other restrictions, and the usage scenarios are diverse
