Motion Parameter Estimation from Global Flow Field Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visually Realistic Mapping of a Planar Environment with Stereo
ISER '00 Experimental Robotics VII
Finding the focus of expansion and estimating range using optical flow images and a matched filter
Machine Vision and Applications
Outlier rejection for cameras on intelligent vehicles
Pattern Recognition Letters
Motion and structure from optical flow
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
Efficient plane detection from a single moving camera
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A Robust Docking Strategy for a Mobile Robot Using Flow Field Divergence
IEEE Transactions on Robotics
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The Focus of Expansion (FoE) sums up all the available information on translational ego-motion for monocular systems. It has also been shown to present interesting features in cognitive research. As such, its localization bears great importance, either for robotic applications, as well as for attention fixation research. It will be shown that the socalled C-Velocity framework can be inversed in order to extract the FoE position from a rough scene structure estimation. This method rely on robust cumulative framework and only exploit the optical flow field relative norm as such, it is robust to angular noise and bias on the absolute optical flow norm.