Application of the background subtraction method and Viola-Jones algorithm for increasing the speed of face tracking in the personality recognition system
https://doi.org/10.23947/2587-8999-2018-2-1-25-32
Abstract
Existing method of automatic tracking of moving objects in the video stream in real time is described in the paper in relation to the task of person’s recognition from his face image. A method of face tracking in the video stream based on a combination of the background subtraction method and the Viola-Jones algorithm for the face area detection in the frame and reducing requirements for computing resources of person’s recognition systems is proposed. Results of testing the proposed face tracking algorithm in the video stream are shown.
Keywords
computer vision,
face detection,
facial recognition,
tracking,
Viola-Jones algorithm,
background subtraction,
real-time video stream processing
Supporting agencies: The research is done within the frame of the government task №. 2.1642.2017/4.6 for the project «Cognitive methods for visualization and analysis of multidimensional data in the modeling of nonlinear dynamic systems».
About the Authors
Alena Aleksandrovna Zakharova
Tomsk Polytechnic University (30, Lenin Avenue, Tomsk, Russia)
Russian Federation
Russian Federation
Zakharova Alena Aleksandrovna, Professor, Doctor of Technical Sciences, School of Computer Science & Robotics of National Research Tomsk Polytechnic University (30, Lenin Avenue, Tomsk, Russia)
Stepan Gennad'yevich Nebaba
Tomsk Polytechnic University (30, Lenin Avenue, Tomsk, Russia)
Russian Federation
Russian Federation
Nebaba Stepan Gennad'yevich, engineer, Candidate of Technical Sciences, School of Computer Science & Robotics of the National Research Tomsk Polytechnic University (30, Lenin Avenue, Tomsk, Russia)
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For citations:
Zakharova A.A., Nebaba S.G. Application of the background subtraction method and Viola-Jones algorithm for increasing the speed of face tracking in the personality recognition system. Computational Mathematics and Information Technologies. 2018;2(1). https://doi.org/10.23947/2587-8999-2018-2-1-25-32
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