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Analysis of existing algorithms for face recognition

Zabashta Aleksandr Iurevich  (Bauman Moscow State Technical University)

Khokhlov Sergei Aleksandrovich  (Assistant, Bauman Moscow State Technical University)

Skorikova Serafima Aleksandrovna  (Bauman Moscow State Technical University)

The problem of developing software for video surveillance systems is ongoing today. It provides the abilities for automatic identification of predefined situations. It gives possibility to reduce mental workload of the operators, and to improve monitoring efficiency. The basis of this work is the research carried out within the work on the graduation project on "Video surveillance software system with situation analysis". One of the functions of this system is to detect of unauthorized access to the secure area. Function is based on the results of face recognition. The main challenges in the implementation of this function are the detection of a face on a video image, the localization of detected face and identification of a person following face recognition. The criteria for the selection a solution for the facial recognition system are been formulated in this paper. The article compares following algorithms on formulated criteria: elastic graph matching, principal component analysis, neural networks and Viola–Jones object detection framework. Selection an algorithm for the graduation project on "Video surveillance software system with situation analysis" is based on the results of comparison. Selected algorithm must maximally meet the requirements of the specification for the graduation project.

Keywords:video surveillance, face recognition, video image, algorithm, neural networks, Viola-Jones method, development, comparison

 

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Citation link:
Zabashta A. I., Khokhlov S. A., Skorikova S. A. Analysis of existing algorithms for face recognition // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2017. -№07-08. -С. 42-45
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