Overview

A proprietary security solutions company promises to enhance security and surveillance at events with its powerful facial-recognition solution.

Challenge

Today, increasing security at events is more important than ever. It is now imperative to identify the vulnerabilities and develop plans to eliminate or mitigate them. Unfortunately, the current methods for securing people and assets at events are not completely successful. Event managers and security professionals need to abandon the old modes of thinking to overcome current security challenges. By incorporating cutting-edge technology across the event, security professionals can prepare event managers and organizers for contingency situations and prevent the worst from happening. A next-gen technology that can fill the current security loopholes at events is facial recognition. Facial recognition is a powerful technology with many applications and one of them is identifying security threats at events and other places.

Solution

Today, more and more organizations are using biometric technology to secure their facilities and events. With biometric technology, they can identify people by fingerprint or iris which can’t be duplicated or stolen, thus providing a greater level of security than many other access control system credentials.

After much forethought and brainstorming as well as several trial runs, the team at Achievion developed a biometric application for face recognition solution that makes it possible to extract features from a person’s photos by means of computer vision.

These features are then used to build a specific watermark and put it on the photos together with additional personal information.The resulting identity document is printed out and can be scanned to verify personal data and efficiently identify the individual.

The facial-recognition solution improves processing result through image stabilization. A feature in cameras, image stabilization minimizes the chances of blurry photos due to vibration or movements in the platform on which the camera rests. The application also allows detection and comparison of facial features. Useful information is provided by the human face. With the biometric application, it is possible to perform fast and reliable detection and comparison of facial features using vision-based computer-human interaction.

An important step in completing several higher-order computer vision tasks, such as face identification and analysis of facial expression, is accurate identification of landmarks within facial images. Our facial-recognition solution ensures this by enabling landmark points identification. For any facial-recognition technology, it is critical to obtain a single coefficient vector for all frames. Our biometric application makes this possible with rotation vector calculations.


  • AWS, OPENCV, TENSORFLOW, R, PYTHON, C++

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