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
A shape deformation algorithm for constrained multidimensional scaling
Date
2015-12-01
Author
Sahillioğlu, Yusuf
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
175
views
0
downloads
Cite This
We present a new Euclidean embedding technique based on volumetric shape registration. Extrinsic representation of the intrinsic geometry of a shape is preferable in various computer graphics applications as it poses only a small degrees of freedom to deal with during processing. A popular Euclidean embedding approach to achieve such a representation is multidimensional scaling (MDS), which, however, distorts the original geometric details drastically. Our method introduces a constraint on the original MDS formulation in order, to preserve the initial geometric details while the input shape is pulled towards its MDS pose using the perfectly accurate bijection in between. The regularizer of this registration framework is chosen in such a way that the system supports large deformations yet remains fast. Consequently, we produce a detail-preserving MDS pose in 90 s for a 53 K-vertex high-resolution mesh on a modest computer. We can also add pairwise point constraints on the deforming shape without any additional cost. Detail-preserving MDS is superior for non-rigid shape retrieval and useful for shape segmentation, as demonstrated.
Subject Keywords
Detail-preserving MDS
,
High-resolution models
,
Canonical form
,
Sparse linear system
,
Retrieval
,
Segmentation
URI
https://hdl.handle.net/11511/34635
Journal
COMPUTERS & GRAPHICS-UK
DOI
https://doi.org/10.1016/j.cag.2015.10.003
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
A Graph-Based Approach for Video Scene Detection
Sakarya, Ufuk; Telatar, Zjya (2008-04-22)
In this paper, a graph-based method for video scene detection is proposed. The method is based on a weighted undirected graph. Each shot is a vertex on the graph. Edge weights among the vertices are evaluated by using spatial and temporal similarities of shots. By using the complete information of the graph, a set of the vertices mostly similar to each other and dissimilar to the others is detected. Temporal continuity constraint is achieved on this set. This set is the first detected video scene. The verti...
A data-centric unsupervised 3D mesh segmentation method
Tümer Sivri, Talya; Sahillioğlu, Yusuf; Department of Modeling and Simulation (2022-12-02)
Modeling, texture mapping, shape compression, simplification, and skeleton extracting are popular and essential topics in mesh segmentation applications. As it serves various purposes in computer science, the mesh segmentation problem is an active and prominent research area. With the help of growing machine learning, deep learning algorithms, and computation power, different methods have been applied to solve the 3D mesh segmentation problem more efficiently. In this thesis, we solve the 3D mesh segmentati...
An algorithm for line matching in an image by mapping into an n-dimensional vector space
Sultanov, Raiymbek; Atakan, Ahmet; Ismailova, Rita (2019-01-01)
This paper proposes a minimal length difference algorithm for construction of a line in an image by solving the problem of optimal contour approximation. In this algorithm, a method for finding interest points is proposed, and the object matching (classification) is done by mapping interest points onto a vector space. In cases where the lines in the representation of the images are not smooth, the algorithm converges rapidly. The results of the experiments showed that for convergence of the contour simplifi...
A Partition Based Method for Spectrum-Preserving Mesh Simplification
Yazgan, Misranur; Sahillioğlu, Yusuf; Department of Computer Engineering (2022-8-29)
When the complexity of a mesh starts introducing high computational costs, mesh simplification methods come into the picture, to reduce the number of elements utilized to represent the mesh. Majority of the simplification methods focus on preserving the appearance of the mesh, ignoring the spectral properties of the differential operators derived from the mesh. The spectrum of the Laplace-Beltrami operator is essential for a large subset of applications in geometry processing. Coarsening a mesh without cons...
A modular regularized variational multiscale proper orthogonal decomposition for incompressible flows
Eroglu, Fatma G.; Kaya Merdan, Songül; Rebholz, Leo G. (Elsevier BV, 2017-10-01)
In this paper, we propose, analyze and test a post-processing implementation of a projection-based variational multiscale (VMS) method with proper orthogonal decomposition (POD) for the incompressible Navier-Stokes equations. The projection-based VMS stabilization is added as a separate post-processing step to the standard POD approximation, and since the stabilization step is completely decoupled, the method can easily be incorporated into existing codes, and stabilization parameters can be tuned independe...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Y. Sahillioğlu, “A shape deformation algorithm for constrained multidimensional scaling,”
COMPUTERS & GRAPHICS-UK
, pp. 156–165, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34635.