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Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Video analysis is a very important tool in video surveillance systems with one or more cameras. Among the most promising features are tracking the movement of objects - tracking. The current state of development in the field of tracking is considered in the work. There are several types of trekking. Pixel Tracking is the tracking of the movement of a specific point (pixel) or group of points on the original video sequence. The result of this process is the trajectory of the pixel, corresponding to the movement of an object in the frame. Matchmoving is a complex process that allows you to create a three-dimensional scene with a digital camera based on the available video sequence, which exactly repeats the movement of a real camera. Motion Capture is a technology designed to determine the position and orientation of a real object in a virtual environment, determining the position and orientation of a real object in space is carried out using special sensors and markers. Each of these types of tracking can be used on its own or as part of more complex processes. The paper develops a modification of the camera motion detection algorithm, which works in the field of Pixel Tracking. The description of the main approaches to motion estimation is given, namely recursive raster algorithms, frequency domain algorithms, optical flow algorithms and block matching methods. The urgency of the work, its purpose and objectives are given. The paper describes a method of arranging blocks in a video sequence frame, which are used to calculate the movement of the camera. Similarity metrics are used to estimate the similarity of the blocks, namely the correlation coefficient. The paper describes the steps of the developed modification of the camera motion detection algorithm. The results of the modification of the camera motion detection algorithm are presented. The result of this work is an indicator of the visual quality of tracking in the form of a 2D image of the camera motion vector. [ABSTRACT FROM AUTHOR]

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper it is proposed basics of a new approach to identify cloning results, conducted in digital images, in additional disturbing influences conditions in a digital image after cloning, that may be considered as lossy compression, add noise, blur, etc. The approach is based on identifying the comparability of the surface parts, which is put into correspondence the analyzed image appropriate clones and its preimage. The surface is determined by the graph of the interpolation spline, approaching the function of the image, and the elements of the image are regarded as the interpolation nodes. It is proved that as the main quantitative characteristics of such comparability is advisable to use the volume of a cylindrical body with generator parallel to the axis OZ, bounded from above corresponding part of the interpolation function graph, bounded below - plane XOY. [ABSTRACT FROM AUTHOR]