Face Recognition
SDK For Surveillance System

taxi trip time prediction analysis
overview face recognition sdk system


Facial recognition is an AI-based system uniquely designed to identify a human face without any physical contact. This advanced way to identify people has taken security to another level. Facial recognition has two vast applications, one of which we will be talking about here. It is used to detect a human face and is used in various CCTV cameras for security reasons. Our client owns a popular treasure gallery involving different high-end artworks; hence, we have built a robust facial recognition security system to monitor the gallery better.

Client Requirement

Our client owns a well-known treasure gallery that displays over 15,000 art pieces such as paintings, sculptures, etc. And their main concern is vandalism, art theft, looting, and smuggling that takes place in several museums or art galleries. Moreover, even the FBI states that art pieces valued at billions of dollars are stolen each year. Therefore, our client needed technical help to preserve cultural heritage and manage the theft. This is when they came across HData Systems to build them a reliable facial recognition SDK to use in their surveillance systems.

client requirements for taxi trip time prediction analysis


  • Our team closely worked with an employee database containing their face pictures. Later, we used NVIDIA Jetson Nano to tune in the device and the surveillance camera at the arrival gate. We then synced it with the gallery's employee access system.

  • Hence, we incorporated face recognition into the gallery's security system. And we created a system to detect and identify employees at the gallery's access point. This system recognizes staff members in the crowd based on their features such as chin, lips, nose, etc. The results then get verified in the employee's database, and if everything looks good, the employee is allowed in.

  • Moreover, we also worked with the art thieves' database that the gallery gave us. We processed video streams from different cameras and later tuned them in with the gallery system. It scans the visitors against the art thieves' database, and if there is any resemblance, the system alerts the management.


  • When the client approached us to build them a facial recognition surveillance system, our team conducted profound research, and after a few brainstorming sessions, we recommended the client create a customized facial recognition SDK to improve their security. We aimed at offering better surveillance in the gallery.



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