A new visual measurement method is proposed to estimate three-dimensional (3D) position of the object on the floor based on a single camera. The camera fixed on a robot is in an inclined position with respect to the...A new visual measurement method is proposed to estimate three-dimensional (3D) position of the object on the floor based on a single camera. The camera fixed on a robot is in an inclined position with respect to the floor. A measurement model with the camera's extrinsic parameters such as the height and pitch angle is described. Single image of a chessboard pattern placed on the floor is enough to calibrate the camera's extrinsic parameters after the camera's intrinsic parameters are calibrated. Then the position of object on the floor can be computed with the measurement model. Furthermore, the height of object can be calculated with the paired-points in the vertical line sharing the same position on the floor. Compared to the conventional method used to estimate the positions on the plane, this method can obtain the 3D positions. The indoor experiment testifies the accuracy and validity of the proposed method.展开更多
Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly...Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.展开更多
Crowd density estimation in wide areas is a challenging problem for visual surveillance. Because of the high risk of degeneration, the safety of public events involving large crowds has always been a major concern. In...Crowd density estimation in wide areas is a challenging problem for visual surveillance. Because of the high risk of degeneration, the safety of public events involving large crowds has always been a major concern. In this paper, we propose a video-based crowd density analysis and prediction system for wide-area surveillance applications. In monocular image sequences, the Accumulated Mosaic Image Difference (AMID) method is applied to extract crowd areas having irregular motion. The specific number of persons and velocity of a crowd can be adequately estimated by our system from the density of crowded areas. Using a multi-camera network, we can obtain predictions of a crowd's density several minutes in advance. The system has been used in real applications, and numerous experiments conducted in real scenes (station, park, plaza) demonstrate the effectiveness and robustness of the proposed method.展开更多
Discrete choice models are widely used in multiple sectors such as transportation, health, energy, and marketing, etc., where the model estimation is usually carried out by using commercial software. Nonetheless, tail...Discrete choice models are widely used in multiple sectors such as transportation, health, energy, and marketing, etc., where the model estimation is usually carried out by using commercial software. Nonetheless, tailored computer codes offer modellers greater flexibility and control of unique modelling situation. Aligned with empirically tailored computing environment, this research discusses the relative performance of six different algorithms of a discrete choice model using three key performance measures: convergence time, number of iterations, and iteration time. The computer codes are developed by using Visual Basic Application (VBA). Maximum likelihood function (MLF) is formulated and the mathematical relationships of gradient and Hessian matrix are analytically derived to carry out the estimation process. The estimated parameter values clearly suggest that convergence criterion and initial guessing of parameters are the two critical factors in determining the overall estimation performance of a custom-built discrete choice model.展开更多
基金supported by National Natural Science Foundation of China(Nos.61273352 and 61473295)National High Technology Research and Development Program of China(863 Program)(No.2015AA042307)Beijing Natural Science Foundation(No.4161002)
文摘A new visual measurement method is proposed to estimate three-dimensional (3D) position of the object on the floor based on a single camera. The camera fixed on a robot is in an inclined position with respect to the floor. A measurement model with the camera's extrinsic parameters such as the height and pitch angle is described. Single image of a chessboard pattern placed on the floor is enough to calibrate the camera's extrinsic parameters after the camera's intrinsic parameters are calibrated. Then the position of object on the floor can be computed with the measurement model. Furthermore, the height of object can be calculated with the paired-points in the vertical line sharing the same position on the floor. Compared to the conventional method used to estimate the positions on the plane, this method can obtain the 3D positions. The indoor experiment testifies the accuracy and validity of the proposed method.
基金This project is supported by National Electric Power Corporation Foundation of China(No.SPKJ010-27).
文摘Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.
基金supported by the National Natural Science Foundation of China under Grant No. 61175007the National Key Technologies R&D Program under Grant No. 2012BAH07B01the National Key Basic Research Program of China (973 Program) under Grant No. 2012CB316302
文摘Crowd density estimation in wide areas is a challenging problem for visual surveillance. Because of the high risk of degeneration, the safety of public events involving large crowds has always been a major concern. In this paper, we propose a video-based crowd density analysis and prediction system for wide-area surveillance applications. In monocular image sequences, the Accumulated Mosaic Image Difference (AMID) method is applied to extract crowd areas having irregular motion. The specific number of persons and velocity of a crowd can be adequately estimated by our system from the density of crowded areas. Using a multi-camera network, we can obtain predictions of a crowd's density several minutes in advance. The system has been used in real applications, and numerous experiments conducted in real scenes (station, park, plaza) demonstrate the effectiveness and robustness of the proposed method.
文摘Discrete choice models are widely used in multiple sectors such as transportation, health, energy, and marketing, etc., where the model estimation is usually carried out by using commercial software. Nonetheless, tailored computer codes offer modellers greater flexibility and control of unique modelling situation. Aligned with empirically tailored computing environment, this research discusses the relative performance of six different algorithms of a discrete choice model using three key performance measures: convergence time, number of iterations, and iteration time. The computer codes are developed by using Visual Basic Application (VBA). Maximum likelihood function (MLF) is formulated and the mathematical relationships of gradient and Hessian matrix are analytically derived to carry out the estimation process. The estimated parameter values clearly suggest that convergence criterion and initial guessing of parameters are the two critical factors in determining the overall estimation performance of a custom-built discrete choice model.