Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
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
6D-vision: fusion of stereo and motion for robust environment perception
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
A Study on Stereo and Motion Data Accuracy for a Moving Platform
Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics
Towards optimal stereo analysis of image sequences
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Spatio-temporal stereo disparity integration
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Improving sub-pixel accuracy for long range stereo
Computer Vision and Image Understanding
Kalman-filter based spatio-temporal disparity integration
Pattern Recognition Letters
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Intelligent vehicle systems need to distinguish which objects are moving and which are static. A static concrete wall lying in the path of a vehicle should be treated differently than a truck moving in front of the vehicle. This paper proposes a new algorithm that addresses this problem, by providing dense dynamic depth information, while coping with real-time constraints. The algorithm models disparity and disparity rate pixel-wise for an entire image. This model is integrated over time and tracked by means of many pixel-wise Kalman filters. This provides better depth estimation results over time, and also provides speed information at each pixel without using optical flow. This simple approach leads to good experimental results for real stereo sequences, by showing an improvement over previous methods.