V.V. Khryashchev - Ph.D. (Eng.), Associate Professor, P.G. Demidov Yaroslavl State University. E-mail: vhr@yandex.ru D.V. Matveev - Post-graduate Student, P.G. Demidov Yaroslavl State University. E-mail: yar_volley@inbox.ru А.А. Lebedev - Master Student, P.G. Demidov Yaroslavl State University. E-mail: lebedevdes@gmail.com I.S. Nenakhov - Post-graduate Student, P.G. Demidov Yaroslavl State University. E-mail: zergoodsound@gmail.com

In the paper discusses three algorithms human detection in the video stream from dome (ceiling) cameras, which based on: motion detection, shape context and histograms of oriented gradients. Algorithm based on histograms of oriented gradients showed the best result among discusses algorithms. However, in the case of a dense arrangement of people in the area of interest these algorithms have shown insufficient results. Algorithms of human heads detection based on boosting and local binary patterns (LBP) proposed to improve the quality of the system of human detection in similar situations. Have been described the results of testing and comparing the considered algorithms. It is found that the best results are obtained by boosting algorithm. In addition, developed and researched an algorithm of post classification true positive and false positive results based on calculation of HOG-features. The application of an additional classifier was allowed to increase the rate of F-value for the algorithm based on the boosting by 6%, and for the algorithm based on LBP by 10%. The described approach can be used for solving some practical problems with the use of video analysis with ceiling cameras: detection of people in the sterile area, the detection of atypical people behavior in the area of interest, control system «smart house», statistical analysis of sporting events in the video data.

 

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