Dr. Sergey N. Yarishev Profile

Dr. Sergey N. Yarishev

at ITMO Univ

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Author

Publications (5)

Proceedings Article | 21 June 2019 Paper

Influence of test bench parameters on determination of CMOS -cameras feature

Dinh Minh, Valery Korotaev, Sergey Yaryshev, Anton Maraev, Ivan Nekrylov, Anna Vasileva

Proceedings Volume 11056, 110562H (2019) https://doi.org/10.1117/12.2526107

KEYWORDS: Video, Cameras, Signal to noise ratio, Photodetectors, Interference (communication), Sensors, Power supplies, Temperature metrology, Light sources and illumination, Visualization

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Proceedings Article | 29 April 2016 Paper

Swarming visual sensor network for real-time multiple object tracking

Yuri Baranov, Sergey Yarishev, Roman Medvedev

Proceedings Volume 9897, 98970L (2016) https://doi.org/10.1117/12.2227536

KEYWORDS: Visualization, Image processing, Cameras, Computing systems, Control systems, Algorithm development, Video processing, Optical tracking, Imaging systems, Distortion, Chemical elements, Error analysis

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Position control of multiple objects is one of the most actual problems in various technology areas. For example, in construction area this problem is represented as multi-point deformation control of bearing constructions in order to prevent collapse, in mining – deformation control of lining constructions, in rescue operations – potential victims and sources of ignition location, in transport – traffic control and traffic violations detection, in robotics –traffic control for organized group of robots and many other problems in different areas. Usage of stationary devices for solving these problems is inappropriately due to complex and variable geometry of control areas. In these cases self-organized systems of moving visual sensors is the best solution. This paper presents a concept of scalable visual sensor network with swarm architecture for multiple object pose estimation and real-time tracking. In this article recent developments of distributed measuring systems were reviewed with consequent investigation of advantages and disadvantages of existing systems, whereupon theoretical principles of design of swarming visual sensor network (SVSN) were declared. To measure object coordinates in the world coordinate system using TV-camera intrinsic (focal length, pixel size, principal point position, distortion) and extrinsic (rotation matrix, translation vector) calibration parameters were needed to be determined. Robust camera calibration was a too resource-intensive task for using moving camera. In this situation position of the camera is usually estimated using a visual mark with known parameters. All measurements were performed in markcentered coordinate systems. In this article a general adaptive algorithm of coordinate conversion of devices with various intrinsic parameters was developed. Various network topologies were reviewed. Minimum error in objet tracking was realized by finding the shortest path between object of tracking and bearing sensor, which set global coordinate system. Weight coefficients were determined by experimental researches of system sensors that are represented in this article. Conclusions obtained from this work are the basement for SVSN prototypes production and its future researches.

Proceedings Article | 22 June 2015 Paper

The research of the nonexcluded air control error component using the optical-electronic system based on the dispersion method

Ivan Nekrylov, Alexandr Timofeev, Sergey Yaryshev, Anton Nikulin

Proceedings Volume 9525, 95253M (2015) https://doi.org/10.1117/12.2184719

KEYWORDS: Control systems, Refractive index, Error control coding, Optoelectronics, Receivers, Temperature metrology, Image sensors, Image filtering, Optical filters, RGB color model

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Proceedings Article | 22 June 2015 Paper

The algorithm for generation of panoramic images for omnidirectional cameras

Vasiliy Lazarenko, Sergey Yarishev, Valeriy Korotaev

Proceedings Volume 9530, 95300K (2015) https://doi.org/10.1117/12.2184584

KEYWORDS: Panoramic photography, Cameras, Calibration, Optical spheres, Distortion, 3D image processing, Spherical lenses, 3D modeling, MATLAB, Image segmentation

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Proceedings Article | 22 June 2015 Paper

Influence of video compression on the measurement error of the television system

A. Sotnik, S. Yarishev, V. Korotaev

Proceedings Volume 9525, 952532 (2015) https://doi.org/10.1117/12.2184576

KEYWORDS: Televisions, Video compression, Image quality, Image processing, Signal processing, Video, Computer programming, Error analysis, Quantization, Image segmentation

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Video data require a very large memory capacity. Optimal ratio quality / volume video encoding method is one of the most actual problem due to the urgent need to transfer large amounts of video over various networks. The technology of digital TV signal compression reduces the amount of data used for video stream representation. Video compression allows effective reduce the stream required for transmission and storage. It is important to take into account the uncertainties caused by compression of the video signal in the case of television measuring systems using. There are a lot digital compression methods. The aim of proposed work is research of video compression influence on the measurement error in television systems. Measurement error of the object parameter is the main characteristic of television measuring systems. Accuracy characterizes the difference between the measured value abd the actual parameter value. Errors caused by the optical system can be selected as a source of error in the television systems measurements. Method of the received video signal processing is also a source of error. Presence of error leads to large distortions in case of compression with constant data stream rate. Presence of errors increases the amount of data required to transmit or record an image frame in case of constant quality. The purpose of the intra-coding is reducing of the spatial redundancy within a frame (or field) of television image. This redundancy caused by the strong correlation between the elements of the image. It is possible to convert an array of image samples into a matrix of coefficients that are not correlated with each other, if one can find corresponding orthogonal transformation. It is possible to apply entropy coding to these uncorrelated coefficients and achieve a reduction in the digital stream. One can select such transformation that most of the matrix coefficients will be almost zero for typical images . Excluding these zero coefficients also possible reducing of the digital stream. Discrete cosine transformation is most widely used among possible orthogonal transformation. Errors of television measuring systems and data compression protocols analyzed In this paper. The main characteristics of measuring systems and detected sources of their error detected. The most effective methods of video compression are determined. The influence of video compression error on television measuring systems was researched. Obtained results will increase the accuracy of the measuring systems. In television image quality measuring system reduces distortion identical distortion in analog systems and specific distortions resulting from the process of coding / decoding digital video signal and errors in the transmission channel. By the distortions associated with encoding / decoding signal include quantization noise, reducing resolution, mosaic effect, "mosquito" effect edging on sharp drops brightness, blur colors, false patterns, the effect of "dirty window" and other defects. The size of video compression algorithms used in television measuring systems based on the image encoding with intra- and inter prediction individual fragments. The process of encoding / decoding image is non-linear in space and in time, because the quality of the playback of a movie at the reception depends on the pre- and post-history of a random, from the preceding and succeeding tracks, which can lead to distortion of the inadequacy of the sub-picture and a corresponding measuring signal.

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