"智能视频监控系统中目标跟踪关键技术研究及系统研制：人工智能与机器学习的应用"

Abstract: In the era of rapid technological advancement, the demand for intelligent systems in various fields is increasing. The concept of "Building a safe city" has become a priority in many major cities, leading to a surge in the video surveillance industry. Intelligent video surveillance, as an innovative advancement in this industry, offers vast opportunities for development and holds significant importance for theoretical research. This paper focuses on the research and implementation of key technologies for target tracking in intelligent video surveillance systems. The integration of artificial intelligence and machine learning techniques plays a crucial role in enhancing the performance and efficiency of target tracking. By utilizing advanced algorithms and models, such as deep learning and convolutional neural networks, the system is able to accurately identify and track targets in real-time. The study explores the challenges and opportunities in developing intelligent video surveillance systems, highlighting the importance of continuous research and innovation in this field. By combining theoretical analysis with practical application, the paper provides valuable insights into the design and implementation of effective target tracking algorithms. Overall, the research presented in this paper contributes to the advancement of intelligent video surveillance systems, paving the way for enhanced security and safety measures in modern cities. Through the utilization of cutting-edge technologies and research methodologies, we can strive towards building a more secure and efficient society for the future.