The Research of Vehicle Tracking Based on Difference Screening and Coordinate Mapping - Advances in Image and Graphics Technologies - page 315

The Research of Vehicle Tracking Based on Difference
Screening and Coordinate Mapping *

Zhang Jun-yuan 1 , Liu Wei-guo 2,3 , Tong Bao-feng 1 , and Wang Nan 1

1 State Key Laboratory of Automotive Simulation and Control
Jilin University, Changchun 130022
2 Zhejiang Key Laboratory of Automobile Safety Technology
Hangzhou , 310000
[e-mail]
3 GEELY AUTOMOBILE RESEARCH INSTITUTE

Abstract. In order to identify vehicle driving cycle by monocular camera and
then offer automotive active safety systems such as ACC (Adaptive Cruise
Control) system, accurate condition identification signal, a difference screen-
ing method based on haar feature is put forward to identify the vehicle and a
method based on coordinate mapping is improved to eliminate the impact that
the changes of pitch angle make on the accuracy of positioning the vehicle, then
combine with Karman filter technology to track vehicles. Finally, the studied
method is used to track the vehicle in an actual video and the test results show
that the method can correctly identify the image of vehicle, and accurately track
the spatial position of vehicle. As a result, the studied method can be used to of-
fer an active safety system like ACC accurate condition identification signal.

Keywords: Vehicle tracking, Monocular camera, Haar training, Coordinate
mapping and Karman filter.

1 Introduction

Vehicle detection technology is one of the important technologies for automotive
active safety. Compared with the radar sensor, camera sensor not only is inexpensive,
but also can provide richer information. In recent years, along with DSP (Digital Sig-
nal Processing) technology developing and the image processing technology matur-
ing, domestic and foreign scholars have made new progress on the research of using
camera sensors for vehicle distance measure.
There are two major categories of front vehicle tracking method by using camera:
one is based on stereo vision, Young-Chul Lim used sub-pixel accuracy to obtain the
front vehicle's position in the image, and then combined with the inverse perspective
projection and the kalman filter to track the spatial position and speed of the vehicle
ahead [1]. Jonghwan Kim first got the location information, according this information
* Fund: Open Fund of Zhejiang Key Laboratory of Automobile Safety Technology
(LHY1109J0565).