RAW格式已经被越来越多的数码相机用户所接受,讨论了使用Adobe Camera Raw后期处理RAW格式图像的一些高级技巧:调整画笔的选择性调整功能、渐变滤镜、色调曲线中Ctrl键的使用、彩色照片转黑白、实现HDR效果、以智能对象打开图像、同时...RAW格式已经被越来越多的数码相机用户所接受,讨论了使用Adobe Camera Raw后期处理RAW格式图像的一些高级技巧:调整画笔的选择性调整功能、渐变滤镜、色调曲线中Ctrl键的使用、彩色照片转黑白、实现HDR效果、以智能对象打开图像、同时处理多张照片等。展开更多
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...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.展开更多
文摘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.
