Optimization of a Tracking System Based on a Network of Cameras

被引：1

作者：

Chigrinskii, V. V. ^{[1
]}

Matveev, I. A. ^{[2
]}

机构：

[1] Moscow Inst Phys & Technol, Dolgoprudnyi 141700, Moscow Oblast, Russia

[2] Russian Acad Sci, Fed Res Ctr Comp Sci & Control, Moscow 119333, Russia

来源：

JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL | 2020年 / 59卷 / 04期

基金：

俄罗斯基础研究基金会;

关键词：

OBJECT DETECTION; IDENTIFICATION;

D O I：

10.1134/S1064230720040127

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Tracking the motion of objects in video sequences is an important problem of computer vision that has a wide range of applications. The key points in tracking systems is the detection of an object and, if it was detected repeatedly, its reidentification. A fast correctly working tracking system that uses a number of cameras is described. The system includes detection and segmentation of objects in images, construction of their appearance descriptors, comparison of each new object with earlier collected objects, and making a decision about their reidentification. The basic system configuration is implemented in which the state-of-the art detection algorithms and models for constructing the appearance descriptors are used as the constituent parts. Based on this, the system as a whole and some of its modules are modified. A computational experiment that quantitatively confirms the advantages of the modified system over the basic system is performed.

引用

页码：583 / 597

页数：15

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