Abstract
In this paper, we proposed an optimized real-time hybrid cooperative multi-camera tracking system for large-scale au-tomate surveillance based on embedded smart cameras including stationary cameras and moving pan/tilt/zoom (PTZ) cameras embedded with TI DSP TMS320DM6446 for intelligent visual analysis. Firstly, the overlapping areas and projection relations between adjacent cameras' field of view (FOV) is calculated. Based on the relations of FOV ob-tained and tracking information of each single camera, a homography based target handover procedure is done for long-term multi-camera tracking. After that, we fully implemented the tracking system on the embedded platform de-veloped by our group. Finally, to reduce the huge computational complexity, a novel hierarchical optimization method is proposed. Experimental results demonstrate the robustness and real-time efficiency in dynamic real-world environ-ments and the computational burden is significantly reduced by 98.84%. Our results demonstrate that our proposed sys-tem is capable of tracking targets effectively and achieve large-scale surveillance with clear detailed close-up visual features capturing and recording in dynamic real-life environments.
Highlights
IntroductionThe last few years have witnessed a widespread of smart cameras [1] in public places for surveillance purposes
The last few years have witnessed a widespread of smart cameras [1] in public places for surveillance purposes.it remain huge challenge for traditional surveillance system based on the framework of single camera and stationary cameras since the task of automated surveillance for public locations, which are usually crowded and wide-area, such as public transport stations, by using independent smart cameras almost impossible due to the limitation of cameras’ field of view [2] and the heavy target occlusion problems [3]
It remain huge challenge for traditional surveillance system based on the framework of single camera and stationary cameras since the task of automated surveillance for public locations, which are usually crowded and wide-area, such as public transport stations, by using independent smart cameras almost impossible due to the limitation of cameras’ field of view [2] and the heavy target occlusion problems [3]
Summary
The last few years have witnessed a widespread of smart cameras [1] in public places for surveillance purposes. A hybrid multi-camera tracking system based on embedded smart cameras including stationary CCTV cameras and moving PTZ cameras is introduced in this paper, in our proposed system, stationary cameras are used for continuous and wide-area monitoring to detect events in important spots or in high places, and once abnormal events are detected via the large-scale view from the fixed cameras, PTZ camera is used for long-term tracking to obtain a close-up capture of the target and record the detailed information and features In this way, by using our proposed framework, a visual surveillance system for large-scale monitoring with detailed close-up visual information capturing is constructed.
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