Automatic Control Systems
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
Residual Images Remove Illumination Artifacts!
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Integrating disparity images by incorporating disparity rate
RobVis'08 Proceedings of the 2nd international conference on Robot vision
6D-vision: fusion of stereo and motion for robust environment perception
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Stereo analysis by hybrid recursive matching for real-time immersive video conferencing
IEEE Transactions on Circuits and Systems for Video Technology
Kalman-filter based spatio-temporal disparity integration
Pattern Recognition Letters
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Using image sequences as input for vision-based algorithms allows the possibility of merging information from previous images into the analysis of the current image. In the context of video-based driver assistance systems, such temporal analysis can lead to the improvement of depth estimation of visible objects. This paper presents a Kalman filter-based approach that focuses on the reduction of uncertainty in disparity maps of image sequences. For each pixel in the current disparity map, we incorporate disparity data from neighbourhoods of corresponding pixels in the immediate previous and the current image frame. Similar approaches have been considered before that also use disparity information from previous images, but without complementing the analysis with data from neighbouring pixels.