Zoltán Fazekas

Calibration and Sensitivity Analysis of a Stereo Vision-Based Driver Assistance System

Az http://intechweb.org/ alatti Books ful alatt kell rakeresni a Stereo Vision cimre es az 1. fejezetre.

A Far-Range Off-line Camera Calibration Method for Stereo Lane Detection Systems

A far-range camera calibration method for vision sensors used in automatic lane detection systems is investigated. Autonomous vehicle guidance based on stereo image acquisition requires the knowledge of the camera parameters, such as camera position, orientation, lens distortion, focal length etc. with high precision. Calibration is performed by placing markers in known positions in front of the vehicle holding the camera(s) and by detecting the location of their images in the acquired snapshots. The parameters are then estimated by minimizing the geometric error in the image. Most of the methods discovered in the literature do not consider errors in the measurement of marker locations. However, a precise marker arrangement for far-range calibration might be expensive to set up. This paper shows that imprecision in the 3D location of the markers can not be tolerated in some practical situations and in such cases, a different optimization is proposed in the calibration of the extrinsic camera parameters (camera position and orientation). A position estimation method is also shown to extract marker positions from far-range laser distance meter measurements. The estimated marker positions are corrected by considering aiming errors, as well. Parameter errors are also estimated. It will be shown that our new calibration and optimization method is expected to result a good accuracy compared to commercial methods.

Experimenting with Routes of Different Geometric Complexity in the Context of Urban Road Environment Detection from Traffic Sign Data

Traffic sign data is used as input for detecting change in the type of urban road environment in which an ego-car is driven. The automatic urban road environment type detection is seen as a useful advanced driver assistance systems (ADAS) function that could be implemented in a straightforward manner relying on an existing ADAS function. Concretely, the traffic signs encountered along the route could be detected and logged by an on-board camera-based traffic sign recognition (TSR) system; and in order to perform the required function, it could be augmented with the change detection method described in the paper. Based on the analysis of the traffic sign and car trajectory data gathered for this preliminary study, the empirical distributions of the traffic signs along routes taken depend also on the geometrical complexity of these routes. A convenient model for describing traffic sign data along a route is a marked Poisson process. A traffic sign log is seen as a realization of such a process, and the minimum description length principle is harnessed to detect change in the road environment type. To test the applicability of this approach for urban routes of different complexity, a number of road environment transitions are looked at, while taking the route complexity into consideration. Finally, the detected changes are compared to ground truth.