Vision-based Target Tracking Technology in Autonomous Vehicles

Abstract

This paper makes an in-depth study of vision-based target tracking technology, discusses the practical and specific applications of Visual Object Tracking in autonomous vehicles, and discusses the progress and challenges of Visual Object Tracking in autonomous vehicles. The ability of autonomous vehicles to accurately track targets in real time is critical to ensuring safe and efficient navigation. Using computer vision algorithms and deep learning techniques, the researchers developed complex systems capable of detecting and tracking objects such as vehicles, pedestrians, and traffic signs. This paper first introduces the background and principle of current target tracking technology, summarizes the current research status of Object Tracking Technology and the practical application and development prospects of visual target tracking technology in autonomous vehicles, and introduces the latest methods and future improvement directions. Overall, this technology has the potential to greatly improve the capabilities of autonomous vehicles, leading to safer and more reliable transportation systems.