Fernando Flores-Mangas
Motion Segmentation Results
Images are bigger than shown here. Zoom in or open in a new window for better detail.
Dots are observations (original trajectory data), circles are motion model predictions, residuals are shown as lines from the center of the predictions to the center of the observations. Colored markers are inliers for the corresponding class. Black crosses are trajectories that fit no model (outliers).
These results illustrate the performance of the algorithm in the presence of a combination of rigidly (the ground) and non-rigidly (the flowers) moving objects. Very few trajectories move coherently in each flower so the algorithm finds more benefit on explaining different parts of the ground (likely due to perspective effects), as opposed to the independent motion of each flower.
Images are bigger than shown here. Zoom in or open in a new window for better detail.
Dots are observations (original trajectory data), circles are motion model predictions, residuals are shown as lines from the center of the predictions to the center of the observations. Colored markers are inliers for the corresponding class. Black crosses are trajectories that fit no model (outliers).
Flower Sequence
These results illustrate the performance of the algorithm in the presence of a combination of rigidly (the ground) and non-rigidly (the flowers) moving objects. Very few trajectories move coherently in each flower so the algorithm finds more benefit on explaining different parts of the ground (likely due to perspective effects), as opposed to the independent motion of each flower.
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