Volume II-3/W5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 459-465, 2015
https://doi.org/10.5194/isprsannals-II-3-W5-459-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 459-465, 2015
https://doi.org/10.5194/isprsannals-II-3-W5-459-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  20 Aug 2015

20 Aug 2015

IMPROVING CAR NAVIGATION WITH A VISION-BASED SYSTEM

H. Kim, K. Choi, and I. Lee H. Kim et al.
  • Dept. of Geoinformatics, The University of Seoul, 163 Seoulsiripdaero, Dongdaemun-gu, Seoul 130-743, Korea

Keywords: Position and Attitude, Car Navigation, Intelligent Vehicle, Single Photo Resection

Abstract. The real-time acquisition of the accurate positions is very important for the proper operations of driver assistance systems or autonomous vehicles. Since the current systems mostly depend on a GPS and map-matching technique, they show poor and unreliable performance in blockage and weak areas of GPS signals. In this study, we propose a vision oriented car navigation method based on sensor fusion with a GPS and in-vehicle sensors. We employed a single photo resection process to derive the position and attitude of the camera and thus those of the car. This image georeferencing results are combined with other sensory data under the sensor fusion framework for more accurate estimation of the positions using an extended Kalman filter. The proposed system estimated the positions with an accuracy of 15 m although GPS signals are not available at all during the entire test drive of 15 minutes. The proposed vision based system can be effectively utilized for the low-cost but high-accurate and reliable navigation systems required for intelligent or autonomous vehicles.