Face Recognition is a practical application of the theory of pattern recognition, which is tasked with automatic localization of faces at pictures and, if necessary, the identification of the person by the face. The function of the identification of the people faces at the digital images is already actively used in the software to manage photo albums (Picasa, iPhoto, etc.).
The task of the face recognition and identification is one of the first practical tasks that encourages the formation and development of the theory of recognition and identification of objects. There are nine categories of objects that match the gnostic areas and cause visual images:
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- objects that can be manipulated (cup, keys, watches, etc.);
- objects which partially manipulated (automobiles, materials, etc.);
- non-manipulated objects (trees, buildings, etc.);
- people;
- facial expressions;
- living creatures (animals, human figure);
- printing characters (letters, symbols, signs);
- handwritten image;
- the characteristics and location of the light sources (moon, sun).
Interest in the procedures underlying the process of the face recognition and identification has always been significant, especially in view of the increasing practical needs: security systems, verification, forensic examination, newsgroups, etc. Despite the clarity of the mundane fact that a human being can easily identify the people faces, it is not obvious how to teach a computer to carry out the procedure, including how to decode and store digital images of faces. Even less clear is the assessment of the faces similarity, including their complex processing. There are several research problems of face recognition:
- neuropsychological model;
- neurophysiological model;
- information – procedural model;
- computer models of recognition.
The problem of face recognition was considered in the early stages of the computer vision. A number of companies for over 40 years has been actively developing first the automated, and now automatic human faces recognition systems: Smith & Wesson (ASID – Automated Suspect Identification System); ImageWare (FaceID); Imagis, Epic Solutions, Spillman, Miros (Trueface ); Vissage Technology (Vissage Gallery); Visionics (FaceIt).
It is necessary for students, writing their research proposal on face recognition systems indicate that such a system can automatically find and identify people in the image files, and video stream.
Key Features:
- the ability to find and identify people at the digital images;
- resistant to changes in the hair, the presence / absence of a mustache and beard, glasses (except sun), age-related changes (except children), turn (30 degrees)
- almost linear scalability of performance when installed on multiprocessor, multicore systems, and computer clusters;
- the ability to give to the images relevant indications (eg, “politics”, “businessman”, etc.) and a brief description for further automatic classification of the processed content;
- the possibility of multi-frame analysis of the video stream, providing the increase of recognition accuracy;
- the results can be output in plain text or XML-document containing information about the position and the size of those found, the results of recognition and time stamps;
Free sample research paper topics on face recognition can became your personal guide through the difficulties of the research project structuring and composing.
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