Full text: Close-range imaging, long-range vision

  
METHOD FOR ON-LINE CALIBRATION FOR AUTOMOBILE OBSTACLE 
DETECTION SYSTEM 
V. A. Knyaz *, 
State Research Institute for Aviation System, 7, Victorenko str., Moscow, Russia 
knyaz@gosniias.msk.ru 
Commission V, WG V/4 
KEY WORDS: Close-range photogrammetry, camera orientation, coded targets, calibration, automation, accuracy, reconstruction. 
ABSTRACT: 
The recent progress in digital photogrammetry creates a backgroun 
applications and in particular for intelligent transportation system. I 
d for applying close-range photogrammetric technique for various 
ntelligent vehicle is often equipped with driver assistance system 
which helps to solve various drivers task including such an important problems as own lane detection and collision prediction. For 
collision prediction driver assistance system has to detect an obstacle in own lane and to determine the position and the dimensions 
of the detected obstacle. The problem of obstacle geometrical parameters determination could be accurately solved by 
photogrammetric system providing high accuracy of 3D measurements for adequate road surface 3D model reconstruction and 
reliable estimation of obstacle parameters. The theoretical analysis and investigation of the images of typical road scenes showed 
that the accuracy of common relative orientation procedure (eliminating vertical parallaxes for corresponding points) results in 
unreliable estimation of relative orientation parameters for poor stereo condition of automobile photogrammetric system. This fact 
caused a low precision of spatial measurements for such a system. 
orientation which provides required precision for tasks of obstacle 
The paper presents methods for on-line calibration and relative 
detecting and estimating. The proposed method has high degree 
of automation and gives high accuracy of 3D measurements approved by investigations in tested area and in real high-way 
conditions. 
1. INTRODUCTION 
Last years vision techniques are widely involved in more and 
more areas of human activity due to such factors as great 
amount of information in vision flow inputting from a video 
camera and a significant progress in image processing. One of 
the challenging fields for vision techniques applying is an 
intelligent transportation system. Cameras installed on an 
automobile are used for various tasks solution beginning with 
parking assistance and finishing with complicated obstacle 
recognition problem. Among the tasks solving by vision system 
are lane departure analysis, ego-motion estimation, road 
geometry reconstruction and analysis, obstacle detection and 
recognition. 
Applying a stereo vision instead of mono-camera system for an 
intelligent vehicle seems to be rather attractive because of 
increasing data flow and possibility for accurate measurement 
performing. One of the important tasks which an intelligent 
vehicle has to solve is obstacle detection in a road and 
estimation of the position and dimensions of the detected 
obstacle. For resolving this problem one needs as possible high 
accuracy of 3D measurements which provides adequate road 
surface 3D model reconstruction and reliable estimation of 
obstacle parameters. So when designing vision system for 
obstacle detection one has to reach contradictory requirements 
of high accuracy of 3D measurements and geometrical 
restrictions caused by vehicle dimensions. 
  
On the one side for obtaining required precision in spatial 
measurements one has to use lenses with long focal length for 
suitable image scale. On the other side the possible basis of the 
stereo-system is restricted by vehicle dimensions. This results 
in bad condition for relative orientation parameters 
determination and therefore in low precision of three- 
dimensional measurements. 
Some methods for mobile system calibration and orientation 
were developed (Knyaz V., 1999), which were based on using 
spatial test field. This technique has demonstrated reasonable 
accuracy of a stereo system orientation parameters estimation 
providing required accuracy for spatial ^ coordinate 
determination of objects belonged to an observed scene. 
The main disadvantage of the proposed technique was a low 
level of automation, this factor decreasing the method 
applicability for an obstacle detection system. 
This paper presents the method for on-line automated 
calibration and relative orientation for photogrammetric system 
based on an automobile. Two CCD video cameras are used as 
image sensors for an obstacle detection system based on 
personal computer equipped with frame grabber and special 
image processing cards for real time image processing. The 
proposed method is based on bundle adjustment procedure, 
using special 2D test scene and special procedure of image 
acquisition for calibration. The automation of calibration 
procedure is provided by using original coded targets as 
* Correspondence: Email: knyaz@gosniias.msk.ru, Telephone: 7-095-1573127, Fax: 7-095-1573900 
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