Paper Info
Title
Sampling Density Criterion For Circular Structured Light 3d Imaging
Abstract
3D reconstruction work has chiefly focused on the accuracy of reconstruction results in computer vision, and efficient 3D functional camera system has been of interest in the field of mobile camera as well. The optimal sampling density, referred to as the minimum sampling rate for 3D or high-dimensional signal reconstruction, is proposed in this paper. There have been many research activities to develop an adaptive sampling theorem beyond the Shannon-Nyquist Sampling Theorem in the areas of signal processing, but sampling theorem for 3D imaging or reconstruction is an open challenging topic and crucial part of our contribution in this paper. We hence propose an approach to sampling rate (lower / upper bound) determination to recover 3D objects (surfaces) represented by a set of circular light patterns, and the criterion for a sampling rate is formulated using geometric characteristics of the light patterns overlaid on the surface. The proposed method is in a sense a foundation for a sampling theorem applied to 3D image processing, by establishing a relationship between frequency components and geometric information of a surface.
Year
DOI
Venue
2017
10.5220/0006147504780483
PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 6
Keywords
Field
DocType
3D Reconstruction, Structured Light Pattern, Sampling Theorem, Geometry
Sampling density,Computer vision,Structured light,Pattern recognition,Computer science,Artificial intelligence
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Deokwoo Lee100.34
Hamid Krim252059.69