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 :
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