video stream

The article considers methods and means of face recognition in a video data stream using elements of machine learning. The main approaches to face identification based on computer vision methods are analyzed, in particular the principal component analysis (PCA) method, the local binary pattern analysis (LBP) method and the linear discriminant analysis (LDA, Fisherfaces) method. The principles of facial feature formation and algorithms for their classification are described.

This paper aims to develop and implement an algorithm and an automated software system for the auto- matic accounting process of external facing panels during transportation on line conveyors. The method described in this paper is designed to simplify the process of production and accounting of wall-facing panels. This method can also serve as a model for implementing other manufacturers. The developed  algorithm consists of the following steps: obtaining a video stream in real-time or from a file and its targeted processing and determining the number of moving objects of interest.

Among the main requirements of modern surveillance systems are stability in the face of negative influences and intellectualization. The purpose of intellectualization is that the surveillance system should perform not only the main functions such as monitoring and stream recording but also have to provide effective stream processing. The requirement for this processing is that the system operation has to be automated, and the operator's influence should be minimal. Modern intelligent surveillance systems require the development of grouping methods.

We propose a structure of special processor implementing feature detection in a video stream based on the SURF algorithm to be used in computer vision systems.

We propose a computer vision system based on multi-processor architecture that uses multi-port memory with equal access to all special microprocessors.

We consider a microcontroller implementation of an algorithm for extracting SURF features of an object in a video stream to be used in a specialized computer vision system.

In these article the mathematical model of multi-agent CFS is proposed for describe of behavior of moving objects, interacting under wireless communication link on 802.11 standard. It has shown that the more important criteria for CFS, consisting of mobile objects, is the stability of communications. The stable transmission rate is achieved by reducing the asymmetry of the link between the cyber-physical components. This will ensure the rhythmical loading of the computing board processors (CPU or / and GPU) on cyber object.