Facial recognition System is a computer application that is able to identify or verify a person from digital image or video. One way to do this is to compare selected facial features from the image and from the database.
Face Detection (the program) is typically used in security systems and can be compared to other biometric systems (e.g. fingerprint or eye iris). Lately it has also become popular as a tool for business identification and advertising.
Some algorithms for face recognition identificeret facial features by extracting landmarks or features from the face image of the subject. For example, the algorithm may analyze the relative position, size and/or shape of the eyes, nose, cheekbones and jaw. These data are then used to search other images with the appropriate parameters. Other algorithms normalize a gallery of face image, and then compress the information about the person, keeping only the data in the image which are useful for face recognition. Then the original image is compared with the available data. One of the earliest successful systems is based on techniques of pattern matching applied to a set of facial features, providing a sort of compressed representation of appearance.
It includes specific algorithms, which can be divided into two basic approaches:
A New trend, developed to achieve higher accuracy, is a three-dimensional face recognition. This technique uses 3D sensors to gather information about the shape of the face. This information is then used to identify distinctive features such as the contour of eye sockets, nose and chin.
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One of the benefits of programs three-dimensional face recognition is that they are not affected by changes in lighting, unlike other options. This technology can also identify from the different range of viewing angles including a profile view. Three-dimensional data points significantly improve the accuracy of face recognition. 3D research is enhanced through the development of sophisticated sensors that improve the work to capture images as three-dimensional images. The sensors work by projecting structured light on the face. Up to a dozen or more of these image sensors can be placed on the same CMOS chip - each one captures a different part of the spectrum.
However, even a perfect method for 3D-matching can be sensitive to facial expressions. For this purpose, a group of researchers at the Technion applied tools from metric geometry to handle expressions as isometries. After this Vision Access created their own solution for three-dimensional face recognition. Later the company was acquired by Bioscrypt Inc., which has developed a version of the program for recognition of human face, known as the 3D FastPass.
The New method is to introduce a method of capturing three-dimensional images using the three tracking cameras that point at different angles. One of them will indicate on the front side of the object, the second – from the side, and the third at an angle. They will all work together to be able to track the person's face in real time and be able to identify it. It is believed that this technology will soon be based any program for face recognition via the camera.
Another new trend uses the visual details of the skin that is captured in standard digital or scanned images. This method, called the analysis of skin texture, turns the unique lines, patterns and spots apparent in human skin, in the mathematical space.
The Tests showed that with the addition of this technology, the efficiency of face recognition can increase by 20-25%.
Another form of receiving input data for face recognition is to use thermal imaging cameras. With this procedure, the camera will only determine the shape of the head, and ignore items such as glasses, hats or makeup. The problem of using thermal images for face recognition lies in the fact that the databases are limited.
Currently, researchers are studying the use of this technology in real life and operational landscapes and at the same time, create a new database of thermal images. The study used low-sensitive ferroelectric electric sensors of low resolution, which is able to long-wave thermal infrared images (LWIR). The results showthe fusion of LWIR and normal visual cameras has great results in the outer probes. This combination can be very powerful facial recognition software for the camera.
While the researchers are working on the latest technologies available only to specialists, the developers of massive applications do not stand on the spot. After we announced the creation of Google Glass, there was a lot of buzz around face recognition and programs for this online. It is believed that this will open many opportunities for users not only to interact with each other and with various objects.
Today there is a large list of interfaces, face recognition, which you can use for your applications. The most common are the following.
Development of Lambda Labs, which provides facial recognition on the placement of eyes, shape of nose and mouth, as well as conducting a gender classification. Available on the official website of the developer.
A Computer facial recognition program on the Internet, which is a perfect replacement Face.com. Currently free of charge.
The Animetrics Face Recognition API can be used to detect faces in photos. Information about facial features or landmarks is returned in the form of coordinates on the image.
To use it, you must have an application created in your account at SkyBiometry. To create a fairly simple registration.
This app uses advanced computer vision technology and data mining to provide 3 core services (detection, recognition, and analysis). The program provides detection and analysis Landmark (23 points), reference point (81 points), attributes: age, gender, glasses, race, and so on.
This is a powerful API for facial recognition. It finds 68 points for a reference image of the front face and 35 for a profile. FaceMark detects landmarks for faces on the image specified by URL or uploaded file, and outputs the result as a JSON file that contains a vector of reference points of the face and points of comparison for each retrieved version.
Intelligent software for emotion recognition, which allows the cameras to read people's micro-expressions, gender and age group. It's the facial recognition in real time, which works when users are watching video on their computers or mobile devices.
This is one of the best alternatives Face.com. Fast, robust and scalable rekognition engine can perform face detection, scanning, OCR, and search. It can be automatically trained using images and tags on Facebook. Because it is focused on social network, this is the best facial recognition software for “Android”.
It is also a powerful and user-friendly interface for detection. It finds faces (both frontal and profile) on the image specified by URL or uploaded as a file, and can find multiple faces in a single photo, and gives a response in JSON format. The image is loaded with the bounding frame for each found entity.
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Alin Trodden - author of the article, editor
"Hi, I'm Alin Trodden. I write texts, read books, and look for impressions. And I'm not bad at telling you about it. I am always happy to participate in interesting projects."
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