Visual Surveillance for Moving Vehicles
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Video-Based Driver Assistance—From Basic Functions to Applications
International Journal of Computer Vision
A Specialized Multibaseline Stereo Technique for Obstacle Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Model-based obstacle detection from image sequences
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
B-spline modeling of road surfaces with an application to free-space estimation
IEEE Transactions on Intelligent Transportation Systems
Recognition of obstacles on structured 3D background
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
A comparative study of two vertical road modelling techniques
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
Motion detection in driving environment using u-v-disparity
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
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Proposes a new approach for vision-based longitudinal and lateral vehicle control. The novel feature of this approach is the use of binocular vision. We integrate two modules consisting of a new, domain-specific, efficient binocular stereo algorithm, and a lane marker detection algorithm, and show that the integration results in a improved performance for each of the modules. Longitudinal control is supported by detecting and measuring the distances to leading vehicles using binocular stereo. The knowledge of the camera geometry with respect to the locally planar road is used to map the images of the road plane in the two camera views into alignment. This allows us to separate image features into those lying in the road plane, e.g. lane markers, and those due to other objects which are dynamically integrated into an obstacle map. Therefore, in contrast with the previous work, we can cope with the difficulties arising from occlusion of lane markers by other vehicles. The detection and measurement of the lane markers provides us with the positional parameters and the road curvature which are needed for lateral vehicle control. Moreover, this information is also used to update the camera geometry with respect to the road, therefore allowing us to cope with the problem of vibrations and road inclination to obtain consistent results from binocular stereo.