Title :
Robust shape recovery from occluding contours using a linear smoother
Author :
Szeliski, Richard ; Weiss, Richard
Author_Institution :
Digital Equipment Corp., Cambridge, MA, USA
Abstract :
Recovering the shape of an object from triangulation fails at occluding contours of smooth objects because the contour generators are view dependent. For three or more views, shape recovery is possible, and several algorithms have been developed for this purpose. The authors´ approach uses a linear smoother to optimally combine all of the measurements available at the contours (and other edges) in all of the images. This allows extraction of a robust and dense estimate of surface shape, and shape information from both surface markings and occluding contours
Keywords :
edge detection; filtering and prediction theory; image recognition; optimisation; linear smoother; occluding contours; optimal measurement combination; robust dense shape estimation; robust shape recovery; surface markings; triangulation; view-dependent contour generators; Cameras; Data mining; Image reconstruction; Information resources; Information science; Robustness; Rotation measurement; Shape; Shape measurement; Smoothing methods; Surface fitting; Surface reconstruction;
Conference_Titel :
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-3880-X
DOI :
10.1109/CVPR.1993.341037