DocumentCode
3192512
Title
Curvature consistency improves local shading analysis
Author
Ferrie, F.P. ; Lagarde, J.
Author_Institution
Comput. Vision & Robotics Lab., McGill Univ., Montreal, Que., Canada
Volume
i
fYear
1990
fDate
16-21 Jun 1990
Firstpage
70
Abstract
The authors describe how a surface reconstruction algorithm based on minimizing the variation of surface curvature can be used to stabilize and correct the results of local shading analysis. The approach is viewpoint independent and applicable to any process that can provide estimates of local surface orientation. The assumptions used in formulating the minimization are derived from standard differential geometry. When applied as a second stage of processing after local shading analysis, the algorithm can recover a close approximation of the true surface orientation under realistic assumptions about image noise. Results are presented that show the performance of the algorithm on synthetic and real data. In particular, they demonstrate how this form of reconstruction can compensate for some of the shape distortion incurred in local shading analysis
Keywords
computerised pattern recognition; computerised picture processing; curvature consistency; curvature variation minimization; differential geometry; local shading analysis; local surface orientation; surface curvature; surface reconstruction; Computer vision; Geometry; Image analysis; Image reconstruction; Intelligent robots; Minimization methods; Noise shaping; Robustness; Shape; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1990. Proceedings., 10th International Conference on
Conference_Location
Atlantic City, NJ
Print_ISBN
0-8186-2062-5
Type
conf
DOI
10.1109/ICPR.1990.118067
Filename
118067
Link To Document