Paper Info
Title
Geometric–photometric approach to monocular shape estimation
Abstract
Monocular, reflectance map-based shape estimation has traditionally relied exclusively on photometric data, but the recently introduced disparity-based photometric stereo (DBPS) and Green's function shape from shading (GSFS) have brought more geometry into it by incorporating a matching equation, and can appropriately be termed a geometric–photometric approach. In DBPS, the matching equation is used for obtaining disparities from the input image pair, while in GSFS it is used for generating the matching image, a uniform disparity field being considered. In both cases, depth can be recovered if one assumes the disparities to result from the displacement of the irradiance pattern over the imaged surface. Starting from the analysis of such displacement under perspective projection, we show that the original DBPS/GSFS formulation must be amended: reconstructions with no free parameters are no longer feasible, but we are able to propose an approximate procedure which yields higher quality estimates, up to a multiplicative factor.
Year
DOI
Venue
2003
10.1016/j.imavis.2003.08.007
Image and Vision Computing
Keywords
Field
DocType
Green's function,Photometric stereo,Physics-based vision,Shape from shading,Structure from motion
Structure from motion,Computer vision,Green's function,Multiplicative function,Photometry (optics),Perspective (graphical),Artificial intelligence,Monocular,Photometric stereo,Mathematics,Free parameter
Journal
Volume
Issue
ISSN
21
12
0262-8856
Citations 
PageRank 
References 
8
0.58
16
Authors
1
Name
Order
Citations
PageRank
José R. A. Torreão15910.18