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.

中文翻译：

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基于摄像机网络的跟踪系统的优化

摘要

跟踪视频序列中对象的运动是计算机视觉的一个重要问题，它具有广泛的应用。跟踪系统中的关键点是对物体的检测，如果反复检测到该物体，则对其进行重新识别。描述了使用许多摄像机的快速正确工作的跟踪系统。该系统包括对图像中的对象进行检测和分割，构造它们的外观描述符，将每个新对象与较早收集的对象进行比较以及对它们的重新标识做出决定。实现了基本系统配置，其中使用了用于构造外观描述符的最新检测算法和模型作为组成部分。基于此，整个系统及其某些模块都进行了修改。