Optimization of a Tracking System Based on a Network of Cameras

Abstract

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.