National NC System Engineering Research Center, Huazhong University of Science and Technology, Wuhan 430074, China.
Sensors (Basel). 2012;12(6):8073-99. doi: 10.3390/s120608073. Epub 2012 Jun 11.
Zoom tracking is an important function in video surveillance, particularly in traffic management and security monitoring. It involves keeping an object of interest in focus during the zoom operation. Zoom tracking is typically achieved by moving the zoom and focus motors in lenses following the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. The main task of a zoom tracking approach is to accurately estimate the trace curve for the specified object. Because a proportional integral derivative (PID) controller has historically been considered to be the best controller in the absence of knowledge of the underlying process and its high-quality performance in motor control, in this paper, we propose a novel feedback zoom tracking (FZT) approach based on the geometric trace curve estimation and PID feedback controller. The performance of this approach is compared with existing zoom tracking methods in digital video surveillance. The real-time implementation results obtained on an actual digital video platform indicate that the developed FZT approach not only solves the traditional one-to-many mapping problem without pre-training but also improves the robustness for tracking moving or switching objects which is the key challenge in video surveillance.
缩放跟踪是视频监控中的一个重要功能，特别是在交通管理和安全监控中。它涉及在缩放操作过程中保持感兴趣的物体处于焦点位置。缩放跟踪通常通过镜头中的缩放和聚焦电机按照所谓的“跟踪曲线”移动来实现，该曲线显示了特定物体距离下聚焦电机位置与缩放电机位置之间的关系。缩放跟踪方法的主要任务是准确估计指定物体的跟踪曲线。由于在缺乏对底层过程的了解的情况下，比例积分微分（PID）控制器被认为是最好的控制器，并且在电机控制方面具有高质量的性能，因此在本文中，我们提出了一种基于几何跟踪曲线估计和 PID 反馈控制器的新型反馈缩放跟踪（FZT）方法。该方法的性能与数字视频监控中的现有缩放跟踪方法进行了比较。在实际的数字视频平台上进行的实时实现结果表明，所开发的 FZT 方法不仅解决了传统的无需预训练的一对多映射问题，而且还提高了对移动或切换物体的跟踪鲁棒性，这是视频监控中的关键挑战。
