Increased Extent of Characteristic Views using Shape-from-Shading for Object Recognition
Author(s) -
P.L. Worthington,
Benoît Huet,
Edwin R. Hancock
Publication year - 1998
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.12.71
Subject(s) - artificial intelligence , computer vision , histogram , object (grammar) , representation (politics) , curvature , shading , computer science , focus (optics) , pattern recognition (psychology) , cognitive neuroscience of visual object recognition , orientation (vector space) , photometric stereo , mathematics , image (mathematics) , computer graphics (images) , geometry , physics , optics , politics , political science , law
This paper investigates the use of shape-from-shading for object recognition. The local surface orientation information recovered using shape-fromshading is shown to provide useful input to an appearance-based object recognition scheme. We consider two representations which may be recovered from shading information - the needle-map, and the local curvature shapeindex - and examine their relative performance for object recognition. Specifically, we use a histogram-comparison technique, and focus upon the relative stability of the representations to small changes of viewpoint. We demonstrate that the needle-map representation allows the view-sphere to be spanned using a significantly smaller number of characteristic views than using either the raw images or the shape index.
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