Active Tracking of Moving Objects with Speed Variations Using a Novel PTZ Camera-based Machine Vision Technique

Abstract

Most existing methods of active tracking focus mainly on slow-moving objects, resulting in limited adaptability to objects with variable speeds. To bridge this research gap, a novel spherical coordinate guided adaptive active tracking (SCAAT) approach based on the pan–tilt–zoom (PTZ) camera machine vision system is proposed in this study. For object detection and tracking, YOLOv5 and DeepSORT are employed in the PTZ vision system. The spherical coordinates and angular speeds of the moving object can be acquired under the spherical coordinate system. For practical application, the start-time and start-angle delay of the PTZ cameras are calibrated, and a speed control equation is conducted in the spherical coordinate system to reduce rapid location deviation between the PTZ and the moving object. To adapt different speeds of the object and avoid camera shaking under different zooms, an adaptive tracking window is designed to keep the object within the camera field of view. Experimental testing has been performed to evaluate the proposed SCAAT method. The results indicate that the SCATT can not only expand the effective following distance and zoom of the PTZ camera, but also effectively improve the accuracy and stability of active tracking for the moving object with large speed variations.