Optimal Sampling for Shape from Focus by Using Gaussian Process Regression

Title
Optimal Sampling for Shape from Focus by Using Gaussian Process Regression
Authors
강민구장훈석윤건우Muhammad Tariq Mahmood
Keywords
Shape from Focus; Gaussian Process Regression
Issue Date
2020-01
Publisher
IEEE ICCE 2020
Abstract
Shape from Focus (SFF) is one of passive optical methods for estimating 3D shape of an object. In SFF, a large number of 2D images with different focus levels are required. The number of images may affect the complexity and the accuracy of the results. In this manuscript, a Gaussian process regression (GPR) method is proposed to get 3D shape from the minimum number of 2D images. The proposed method (SFF.GPR) is applied to fit focus curves, which are obtained by applying one of focus measure operators. Experimental results demonstrate the effectiveness of the proposed method.
URI
http://pubs.kist.re.kr/handle/201004/70452
ISSN
-
Appears in Collections:
KIST Publication > Conference Paper
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