Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Multi-baseline stereo correction for silhouette-based 3D model reconstruction from multiple images
Date
2001-01-25
Author
Mulayim, AY
Atalay, Mehmet Volkan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
169
views
0
downloads
Cite This
Silhouette based reconstruction algorithm is simple and robust for 3D volume estimation of an object. However? it has two main drawbacks: insufficient number of viewing positions and the inability to detect concavity regions. Starting from an initial convex hull of the object to be modeled which is generated by a silhouette based reconstruction, an algorithm based on photoconsistency is described. The algorithm basically carves the excess volume elements using the multi-baseline stereo information. Result of the described algorithm is demostrated on a sythesized object in an artificial environment.
Subject Keywords
3D object modeling
,
Silhouette based reconstruction
,
Photoconsistency
,
Multi-baseline stereo
URI
https://hdl.handle.net/11511/38811
DOI
https://doi.org/10.1117/12.424900
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Extraction of 3D transform and scale invariant patches from range scans
Akagunduz, Erdern; Ulusoy, İlkay (2007-06-22)
An algorithm is proposed to extract transformation and scale invariant 3D fundamental elements from the surface structure of 3D range scan data. The surface is described by mean and Gaussian curvature values at every data point at various scales and a scale-space search is performed in order to extract the fundamental structures and to estimate the location and the scale of each fundamental structure. The extracted fundamental structures can later be used as nodes in a topological graph where the links betw...
Feature extraction from acoustic and hyperspectral data by 2d local discriminant bases search
Kalkan, Habil; Kalkan, Habil; Department of Information Systems (2008)
In this thesis, a feature extraction algorithm based on 2D Local Discriminant Bases (LDB) search is developed for acoustic and hyperspectral data. The developed algorithm extracts the relevant features by both eliminating the irrelevant ones and/or by merging the ones that do not provide extra information on their own. It is implemented on real world data to separate aflatoxin contaminated or high risk hazelnuts from the sound ones by using impact acoustic and hyperspectral data. Impact acoustics data is us...
3-D motion estimation of rigid objects for video coding applications using an improved iterative version of the E-matrix method
Alatan, Abdullah Aydın (1998-02-01)
As an alternative to current two-dimensional (2-D) motion models, a robust three-dimensional (3-D) motion estimation method is proposed to be utilized in object-based video coding applications, Since the popular E-matrix method is well known for its susceptibility to input errors, a performance indicator, which tests the validity of the estimated 3-D motion parameters both explicitly and implicitly, is defined. This indicator is utilized within the RANSAC method to obtain a robust set of 2-D motion correspo...
Multi-image region growing for integrating disparity maps
Leloglu, UĞUR MURAT; Halıcı, Uğur (1999-01-01)
In this paper, a multi-image region growing algorithm to obtain planar 3-D surfaces in the object space from multiple dense disparity maps, is presented. A surface patch is represented by a plane equation and a set of pixels in multiple images. The union of back projections of all pixels in the set onto the infinite plane, forms the surface patch. Thanks to that hybrid representation of planar surfaces, region growing (both region aggregation and region merging) is performed on all images simultaneously. Pl...
Nonintrusive model order reduction for cross-diffusion systems
Karasözen, Bülent; Mülayim, Gülden; Uzunca, Murat (2022-12-01)
In this paper, we investigate tensor based nonintrusive reduced-order models (ROMs) for parametric cross-diffusion equations. The full-order model (FOM) consists of ordinary differential equations (ODEs) in matrix or tensor form resulting from finite difference discretization of the differential operators by taking the advantage of Kronecker structure. The matrix/tensor differential equations are integrated in time with the implicit–explicit (IMEX) Euler method. The reduced bases, relying on a finite sample...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
A. Mulayim and M. V. Atalay, “Multi-baseline stereo correction for silhouette-based 3D model reconstruction from multiple images,” 2001, vol. 4298, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38811.