Person Tracking System

Person tracking systems aim to automatically locate and follow individuals, primarily using visual data from cameras or alternative sensors like Bluetooth and ultrasound. Current research focuses on improving accuracy and robustness, particularly in challenging environments like crowded scenes or across multiple camera views, employing techniques such as deep learning models (e.g., YOLO-based architectures and correlation filters) and cross-modality data fusion. These advancements have implications for security and surveillance, industrial safety monitoring, and also raise important privacy considerations, leading to research on methods to mitigate detection.