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.
The vision of the surrounding and people that are within eyeshot influences the human well-being and safety. The rationale of system development that allows recognizing faces from difficult perspectives online and informing timely about approaching people is undisputed. The manuscript describes the methods of automatic detection of equilibrium face points in the bitmap image and methods of forming 3D face model. The optimal search algorithm for equilibrium points has been chosen. The method of forming 3D face model basing on a single bitmap image and building up the face image rotated to the preset angle has been proposed. The algorithm for estimating the angle and algorithm of the face image rotation have been implemented. The manuscript also reviews the existing methods of forming 3D face model. The algorithm for the formation of 3D face model from a single bitmap image and a set of individual 3D models have been proposed as well as the algorithm for forming different face angles with the calculated 3D face model aimed to create biometric vectors cluster. Operation results of the algorithm for face images formation from different angles have been presented.
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