期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2006
卷号：XXXVI Part 7
出版社：Copernicus Publications
摘要：Measuring positions, velocities and accelerations/decelerations of individual vehicles in congested traffic with standard traffic moni- toring equipment, such as inductive loops, are not feasible. The behavior of drivers in the different traffi c situations, as re-quired for microscopic traffi c .ow models, is still not sufficiently known. Remote sensing and computer vision technology are recently being used to solve this problem. In this study we use video images taken from a helicopter above a fixed point of the highway. We address the problem of tracking the movement of previously detected vehicles through a stabilized video sequence. We combine two approaches, optical .ow and matching based tracking, improve them by adding constraints and using scale space. Feature elements, i.e. the corners, lines, regions and outlines of each car, are extracted first. Then, optical-. ow is used to find for each pixel in the interior of a car the corresponding pixel in the next image, by inserting the brightness model. Normalized cross correlation matching is used at the corners of the car. Different pixels are used for solving the aperture problem of optical . ow and for the template matching area: neighboring pixel and feature pixels. The image boundary, road line boundaries, maximum speed of the car, and positions of surrounding cars are used as constraints. Ideally, the result of each pixel of a car should give the same displacement because cars are rigid objects
关键词：Optical Flow; Tracking; Feature detection; Matching; Region based; Feature based
