This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information...This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information gathering robotic system in unknown environment. Here, each mobile robot is not possible to know its own position. It can only estimate its own position by using the measurement value including white noise acquired by two omnidirectional cameras mounted on it. Each mobile robot is able to obtain the distance to those robots observed from the images of two omnidirectional cameras while making calibration during moving but not in advance. Simulation of three robots moving straightly shows the effectiveness of the proposed algorithm.展开更多
In this paper,we use 1D rotating objects to calibrate camera.The calibration object has three collinear points.It is not necessary for the object to rotate around one of its endpoints as before;instead,it rotates arou...In this paper,we use 1D rotating objects to calibrate camera.The calibration object has three collinear points.It is not necessary for the object to rotate around one of its endpoints as before;instead,it rotates around the middle point in a plane.In this instance,we can use two calibration constraints to compute the intrinsic parameters of a camera.In addition,when the 1D object moves in a plane randomly,the proposed technique remains valid to compute the intrinsic parameters of a camera.Experiments with simulated data as well as with real images show that our technique is accurate and robust.展开更多
Video based surveillance systems have been widely used on freeway for traffic monitoring, as the cameras can provide the most intuitionistic information. In order to manage all the traffic videos automatically, in thi...Video based surveillance systems have been widely used on freeway for traffic monitoring, as the cameras can provide the most intuitionistic information. In order to manage all the traffic videos automatically, in this paper, a distributed real-time auto- surveillance system is presented. The freeway traffic videos are taken as input video from Pan Tilt Zoom （PTZ） camera, and then produces an analysis of the states and activity of the vehicles in the region of interested （ROI）, if there is any abnormal instance, an alarm and corresponding traffic video are sent to awake surveillants by Ethernet. To achieve this functionality, our system relies on three main procedures. The first one initializes the system. It detects the ROI of the scene, and performs the camera calibration to remove the perspective effect of the incoming image. The second one segments moving vehicles from the images, eliminate shadow and tracks them real-time. It uses a set of methods to obtain the background of the image, extracts the moving regions and tracks these moving regions by matching them between frames of the video sequence to obtain high-level information such as color, size, velocity, and trajectories of moving vehicles. In the third procedure, activities of vehicles are analyzed based on a series of preset situations which would happen on freeway. The detail information of each vehicle and the global statistical information are checked to find out any abnormal instance, and then triggered an alarm. We present details of the system, together with experiment results which demonstrate the accuracy and time responses.展开更多
文摘This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information gathering robotic system in unknown environment. Here, each mobile robot is not possible to know its own position. It can only estimate its own position by using the measurement value including white noise acquired by two omnidirectional cameras mounted on it. Each mobile robot is able to obtain the distance to those robots observed from the images of two omnidirectional cameras while making calibration during moving but not in advance. Simulation of three robots moving straightly shows the effectiveness of the proposed algorithm.
文摘In this paper,we use 1D rotating objects to calibrate camera.The calibration object has three collinear points.It is not necessary for the object to rotate around one of its endpoints as before;instead,it rotates around the middle point in a plane.In this instance,we can use two calibration constraints to compute the intrinsic parameters of a camera.In addition,when the 1D object moves in a plane randomly,the proposed technique remains valid to compute the intrinsic parameters of a camera.Experiments with simulated data as well as with real images show that our technique is accurate and robust.
文摘Video based surveillance systems have been widely used on freeway for traffic monitoring, as the cameras can provide the most intuitionistic information. In order to manage all the traffic videos automatically, in this paper, a distributed real-time auto- surveillance system is presented. The freeway traffic videos are taken as input video from Pan Tilt Zoom （PTZ） camera, and then produces an analysis of the states and activity of the vehicles in the region of interested （ROI）, if there is any abnormal instance, an alarm and corresponding traffic video are sent to awake surveillants by Ethernet. To achieve this functionality, our system relies on three main procedures. The first one initializes the system. It detects the ROI of the scene, and performs the camera calibration to remove the perspective effect of the incoming image. The second one segments moving vehicles from the images, eliminate shadow and tracks them real-time. It uses a set of methods to obtain the background of the image, extracts the moving regions and tracks these moving regions by matching them between frames of the video sequence to obtain high-level information such as color, size, velocity, and trajectories of moving vehicles. In the third procedure, activities of vehicles are analyzed based on a series of preset situations which would happen on freeway. The detail information of each vehicle and the global statistical information are checked to find out any abnormal instance, and then triggered an alarm. We present details of the system, together with experiment results which demonstrate the accuracy and time responses.
