Abstract: With the development of urbanization and technology, the importance of modern city surveillance system comes to the fore. Object tracking technology, as the key to improve the system analysis performance, currently still relies on high-density surveillance facilities and powerful computing capabilities, and is susceptible to the influence of complex scene turnover and object occlusion, which requires manual intervention to ensure tracking efficiency and stability. Therefore, this paper proposes an innovative technical framework, which replaces the traditional passive tracking technology route with a multi-surveillance dynamic active parsing approach by utilizing techniques such as surveillance device parameterization, surveillance system visible range mapping, and the integration of real and predictive scenarios. Experimental results indicate that the proposed technology can reduce the processing time of tracking task by 1/48 of the original one, and decrease the number of analysis devices from 360 to 75, which significantly reduces the difficulty of system deployment, improves the tracking efficiency, and provides a new direction for the intelligent application of modern city surveillance systems.