Facial recognition systems

Anyone who has seen the TV show "Las Vegas" has seen facial recognition software in action. In any given episode, the security department at the fictional Montecito Hotel and Casino uses its video surveillance system to pull an image of a card counter, thief or blacklisted individual. It then runs that image through the database to find a match and identify the person. By the end of the hour, all bad guys are escorted from the casino or thrown in jail. But what looks so easy on TV doesn't always translate as well in the real world.
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How to build a face detection and recognition system

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Facial Recognition

Today I would like to share some ideas about how to develop a face recognition-based biometric identification system using OpenCV library, DLib and real-time streaming via video camera. First, it must detect a face. Then, it must recognize that face nearly instantaneously. Finally, it must take whatever further action is required, such as allowing access for an approved user. My teammate in the video explains the idea in general, and below you can read a more detailed description. The facial recognition process begins with an application for the camera, installed on any compatible device in communication with said camera. The application is programmed in Golang , and works with both Raspbian and Ubuntu as a local console app.
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How Facial Recognition Systems Work

The INTERPOL Face Recognition System is an automated biometric software application capable of uniquely identifying or verifying a person by comparing and analysing patterns based on their facial features and contours. This is a relatively new biometric which is being introduced by police and other agencies around the world. As this is still in its infancy in most countries, standards and best practices are still in the process of being created, and INTERPOL is contributing to this.
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Using the human face as a key to security, biometric face recognition technology has received significant attention in the past several years due to its potential for a wide variety of applications in both law enforcement and non-law enforcement. Face images can be captured from a distance without touching the person being identified, and the identification does not require interacting with the person. In addition, face recognition serves the crime deterrent purpose because face images that have been recorded and archived can later help identify a person. NEC NeoFace technology's strength lies in its tolerance of poor quality.
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