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In this paper, a novel method is presented to generate tex-tured CAD model of outdoor urban environment using a vehicle-borne sensor system. In data measurement, three single-row laser range scanners and six line cameras are mounted on a measurement vehicle, which has been equipped with a GPS/INS/Odometer based navigation system. Laser range and line images(More)
—In this research, we propose a novel system for tracking pedestrians in a wide and open area, such as a shopping mall and exhibition hall, using a number of single-row laser-range scanners (LD-A), which have a profiling rate of 10 Hz and a scanning angle of 270. LD-As are set directly on the floor doing horizontal scanning at an elevation of about 20 cm(More)
Laser-based people tracking systems have been developed for mobile robotic, and intelligent surveillance areas. Existing systems rely on laser point clustering method to extract object locations. However, for dense crowd tracking, laser points of different objects are often interlaced and undistinguishable due to measurement noise and they can not provide(More)
Three dimension data are in great demand for the various applications such as 3D GIS, navigation, digital archive, simulation, computer games, and so on. In order to represent space in details, it is indispensable to acquire 3D shape and texture together. However, there still lacks a reliable, quick, and handy method of acquiring three dimension data at(More)
In this research, a novel method of reconstructing 3D urban scene using vehicle-borne laser range scanners is proposed. Two one-dimensional laser range scanners are mounted on the roof of a vehicle, doing horizontal and vertical profiling respectively. As the vehicle moves ahead, a horizontal and vertical range profile of the surroundings is captured at(More)
In this research, a novel vehicle-borne system of measuring three-dimensional (3-D) urban data using single-row laser range scanners is proposed. Two single-row laser range scanners are mounted on the roof of a vehicle, doing horizontal and vertical profiling respectively. As the vehicle moves ahead, a horizontal and a vertical range profile of the(More)
Our final goal is to enhance driver safety in a dynamic and unstructured large environment, where the intelligent vehicle might be close to other moving objects, so that high accuracy is required for understanding the situation of each object. We want to detect the moving objects in the surroundings, and track their states, such as speed, direction, and(More)