Readings in computer vision: issues, problems, principles, and paradigms
Fitting Parameterized Three-Dimensional Models to Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mobile Robot Localisation Using Active Vision
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Real-Time Simultaneous Localisation and Mapping with a Single Camera
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
| Hi-index | 0.00 |
For the realization of driving assistance and safety systems vehicles are being increasingly equipped with sensors. As these sensors contribute a lot to the cost of the whole package and at the same time consume some space, car manufacturers try to integrate applications that make use of already integrated sensors. This leads to the fact that each sensor has to fulfil several functions at once and to deliver information to different applications. When estimating very precise positioning information of a vehicle existing sensors have to be combined in an appropriate way to avoid the integration of additional sensors into the vehicle. The GPS receiver, which is coupled with the navigation assistant of the vehicle, delivers a rough positioning information, which has to be improved using already available information from other built in sensors. The approach discussed in this paper uses a model-based method to compare building models obtained from maps with video image information. We will examine, if the explorative coupling of sensors can deliver an appropriate evaluation criteria for positioning hypotheses.