Feature point tracking over a video sequence fails when the points go out of the field of view or behind other objects. Motivated by 3-D reconstruction applications, we extend such interrupted tracking by imposing the constraint that under the ane camera model feature trajectories should be in an ane space in the parameter space. Our method consists of iterations for optimally extending the trajectories so that they are compatible with the estimated ane space and optimally estimating the ane space from the extended trajectories, coupled with an outlier removal process based on a statistical model of image noise. Using real video images, we demonstrate that our method can restore suciently many trajectories for accurate and detailed 3-D reconstruction.
['Yasuyuki Sugaya', 'Kenichi Kanatani']
Extending Interrupted Feature Point Tracking for 3-D Affine Reconstruction