Performance of optical flow techniques
International Journal of Computer Vision
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Vision and Applications
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation
International Journal of Computer Vision
Real-Time Correlation-Based Stereo Vision with Reduced Border Errors
International Journal of Computer Vision
Frame Decimation for Structure and Motion
SMILE '00 Revised Papers from Second European Workshop on 3D Structure from Multiple Images of Large-Scale Environments
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Belief Propagation on the GPU for Stereo Vision
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Real-time stereo vision using semi-global matching on programmable graphics hardware
ACM SIGGRAPH 2006 Sketches
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Automatic free parking space detection by using motion stereo-based 3D reconstruction
Machine Vision and Applications
A survey of motion-parallax-based 3-D reconstruction algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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The ability of generating and interpreting a three-dimensional representation of the environment in real-time is one of the key technologies for autonomous vehicles. While active sensors like ultrasounds have been commercially used, their cost and precision is not favorable. On the other hand, integrating passive sensors, like video cameras, in modern vehicles is quite appealing especially because of their low cost. However, image processing requires reliable real-time algorithms to retrieve depth from visual information. In addition, the limited processing power in automobiles and other mobile platforms makes this problem even more challenging. In this paper we introduce a parking assistance system which relies on dense motion-stereo to compute depth maps of the observed environment in real-time. The flexibility and robustness of our method is showcased with different applications: automatic parking slot detection, a collision warning for the pivoting ranges of the doors and an image-based rendering technique to visualize the environment around the host vehicle. We evaluate the accuracy and reliability of our system and provide quantitative and qualitative results. A comparison to ultrasound and feature-based motion-stereo solutions shows that our approach is more reliable.