Camera Network

Camera networks are systems of multiple cameras working together to achieve enhanced visual perception and analysis, primarily focusing on object tracking, identification, and behavior understanding across wide areas. Current research emphasizes developing robust algorithms for tasks like person and vehicle re-identification, often employing deep learning models (e.g., transformer networks, spatial-temporal fusion networks) and addressing challenges such as camera calibration, noise reduction, and privacy preservation through edge computing. These advancements have significant implications for various applications, including public safety, urban planning, healthcare monitoring (e.g., assessing cognitive impairment), and robotics, by enabling more efficient and accurate analysis of visual data from complex environments.