Most sensors or cameras discussed in the sensor network community are usually 3D homogeneous, even though their2 D coverage areas in the ground plane are heterogeneous. Meanwhile, observed objects of camera networks a...Most sensors or cameras discussed in the sensor network community are usually 3D homogeneous, even though their2 D coverage areas in the ground plane are heterogeneous. Meanwhile, observed objects of camera networks are usually simplified as 2D points in previous literature. However in actual application scenes, not only cameras are always heterogeneous with different height and action radiuses, but also the observed objects are with 3D features（i.e., height）. This paper presents a sensor planning formulation addressing the efficiency enhancement of visual tracking in 3D heterogeneous camera networks that track and detect people traversing a region. The problem of sensor planning consists of three issues：（i） how to model the 3D heterogeneous cameras;（ii） how to rank the visibility, which ensures that the object of interest is visible in a camera＇s field of view;（iii） how to reconfigure the 3D viewing orientations of the cameras. This paper studies the geometric properties of 3D heterogeneous camera networks and addresses an evaluation formulation to rank the visibility of observed objects. Then a sensor planning method is proposed to improve the efficiency of visual tracking. Finally, the numerical results show that the proposed method can improve the tracking performance of the system compared to the conventional strategies.展开更多
经颅磁刺激(transcranial magnetic stimulation, TMS)是一种神经调制方法,临床中凭借医生经验手动确定TMS线圈摆放位姿,导致线圈摆放位置和姿态不准确且重复定位精度差。针对上述问题,提出一种TMS线圈机器人辅助定位系统,使用RGB相机...经颅磁刺激(transcranial magnetic stimulation, TMS)是一种神经调制方法,临床中凭借医生经验手动确定TMS线圈摆放位姿,导致线圈摆放位置和姿态不准确且重复定位精度差。针对上述问题,提出一种TMS线圈机器人辅助定位系统,使用RGB相机替代导航系统中双目红外相机,采用一种基于神经网络的无标志物TMS线圈机器人辅助定位方法。搭建神经网络实现相机空间线圈姿态到操作臂空间关节角度的映射,并通过仿真数据训练验证了该神经网络架构适用于TMS线圈位姿摆放问题。随后,通过实验验证了该方法的可行性,同时表明训练的神经网络针对TMS线圈定位任务具有良好的泛化能力。最后,在笛卡儿空间的位姿验证结果显示TMS线圈三维位置平均误差为2.16 mm,总体姿态误差为0.055 rad,使用RGB相机的TMS线圈机器人辅助定位系统在精度上达到了与其他使用双目红外相机的科研或商用系统相同的水平,满足TMS临床治疗要求,具备临床应用的可行性。展开更多
This paper presents an automatic system of vehicle number-plate recognition based on neural networks. In this system, location of number-plate and recognition of characters in number-plate can be automatically complet...This paper presents an automatic system of vehicle number-plate recognition based on neural networks. In this system, location of number-plate and recognition of characters in number-plate can be automatically completed. Pixel colors of Number-plate area are classified using neural network, then color features are extracted by analyzing scanning lines of the cross-section of number-plate. It takes full use of number-plate color features to locate number-plate. Characters in number-plate can be effectively recognized using the neural networks. Experimental results show that the correct rate of number-plate location is close to 100%, and the time of number-plate location is less than 1 second. Moreover, recognition rate of characters is improved due to the known number-plate type. It is also observed that this system is not sensitive to variations of weather, illumination and vehicle speed. In addition, and also the size of number-plate need not to be known in prior. This system is of crucial significance to apply and spread the automatic system of vehicle number-plate recognition.展开更多
基金supported by the National Natural Science Foundationof China(61100207)the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(2014BAK14B03)+1 种基金the Fundamental Research Funds for the Central Universities(2013PT132013XZ12)
文摘Most sensors or cameras discussed in the sensor network community are usually 3D homogeneous, even though their2 D coverage areas in the ground plane are heterogeneous. Meanwhile, observed objects of camera networks are usually simplified as 2D points in previous literature. However in actual application scenes, not only cameras are always heterogeneous with different height and action radiuses, but also the observed objects are with 3D features（i.e., height）. This paper presents a sensor planning formulation addressing the efficiency enhancement of visual tracking in 3D heterogeneous camera networks that track and detect people traversing a region. The problem of sensor planning consists of three issues：（i） how to model the 3D heterogeneous cameras;（ii） how to rank the visibility, which ensures that the object of interest is visible in a camera＇s field of view;（iii） how to reconfigure the 3D viewing orientations of the cameras. This paper studies the geometric properties of 3D heterogeneous camera networks and addresses an evaluation formulation to rank the visibility of observed objects. Then a sensor planning method is proposed to improve the efficiency of visual tracking. Finally, the numerical results show that the proposed method can improve the tracking performance of the system compared to the conventional strategies.
基金the Key Development Plan Project of Science and Technology (No.991p0111).
文摘This paper presents an automatic system of vehicle number-plate recognition based on neural networks. In this system, location of number-plate and recognition of characters in number-plate can be automatically completed. Pixel colors of Number-plate area are classified using neural network, then color features are extracted by analyzing scanning lines of the cross-section of number-plate. It takes full use of number-plate color features to locate number-plate. Characters in number-plate can be effectively recognized using the neural networks. Experimental results show that the correct rate of number-plate location is close to 100%, and the time of number-plate location is less than 1 second. Moreover, recognition rate of characters is improved due to the known number-plate type. It is also observed that this system is not sensitive to variations of weather, illumination and vehicle speed. In addition, and also the size of number-plate need not to be known in prior. This system is of crucial significance to apply and spread the automatic system of vehicle number-plate recognition.
