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
Disconnected Skeleton: Shape at Its Absolute Scale
Download
index.pdf
Date
2008-12-01
Author
Aslan, Cagri
Erdem, Aykut
Erdem, Erkut
Tarı, Zehra Sibel
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
190
views
83
downloads
Cite This
We present a new skeletal representation along with a matching framework to address the deformable shape recognition problem. The disconnectedness arises as a result of excessive regularization that we use to describe a shape at an attainably coarse scale. Our motivation is to rely on the stable properties of the shape instead of inaccurately measured secondary details. The new representation does not suffer from the common instability problems of traditional connected skeletons and the matching process gives quite successful results on a diverse database of 2D shapes. An important difference of our approach from the conventional use of the skeleton is that we replace the local coordinate frame with a global euclidean frame supported by additional mechanisms to handle articulations and local boundary deformations. As a result, we can produce descriptions that are sensitive to any combination of changes in scale, position, orientation, and articulation, as well as invariant ones.
Subject Keywords
Computational Theory and Mathematics
,
Software
,
Applied Mathematics
,
Artificial Intelligence
,
Computer Vision and Pattern Recognition
URI
https://hdl.handle.net/11511/58038
Journal
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
DOI
https://doi.org/10.1109/tpami.2007.70842
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
Imbalance Problems in Object Detection: A Review.
Oksuz, Kemal; Cam, Baris Can; Kalkan, Sinan; Akbaş, Emre (Institute of Electrical and Electronics Engineers (IEEE), 2020-03-19)
In this paper, we present a comprehensive review of the imbalance problems in object detection. To analyze the problems in a systematic manner, we introduce a problem-based taxonomy. Following this taxonomy, we discuss each problem in depth and present a unifying yet critical perspective on the solutions in the literature. In addition, we identify major open issues regarding the existing imbalance problems as well as imbalance problems that have not been discussed before. Moreover, in order to keep our revi...
Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?
KRÜGER, Norbert; JANSSEN, Peter; Kalkan, Sinan; LAPPE, Markus; LEONARDİS, Ales; PİATER, Justus; Rodriguez-Sanchez, Antonio J.; WİSKOTT, Laurenz (Institute of Electrical and Electronics Engineers (IEEE), 2013-08-01)
Computational modeling of the primate visual system yields insights of potential relevance to some of the challenges that computer vision is facing, such as object recognition and categorization, motion detection and activity recognition, or vision-based navigation and manipulation. This paper reviews some functional principles and structures that are generally thought to underlie the primate visual cortex, and attempts to extract biological principles that could further advance computer vision research. Or...
An axis-based representation for recognition
Aslan, C; Tarı, Zehra Sibel (2005-01-01)
We present a new axis-hased shape representation scheme along with a matching framework to address the problem of generic shape recognition. The main idea is to define the relative spatial arrangement of local symmetry axes and their metric properties in a shape centered coordinate frame. The resulting descriptions are invariant to scale, rotation, small changes in viewpoint and articulations. Symmetry points are extracted from a surface whose level curves roughly mimic the motion by curvature. By increasin...
Modeling of dislocation-grain boundary interactions in a strain gradient crystal plasticity framework
ÖZDEMİR, İZZET; Yalçınkaya, Tuncay (Springer Science and Business Media LLC, 2014-08-01)
This paper focuses on the continuum scale modeling of dislocation-grain boundary interactions and enriches a particular strain gradient crystal plasticity formulation (convex counter-part of Yal double dagger inkaya et al., J Mech Phys Solids 59:1-17, 2011; Int J Solids Struct 49:2625-2636, 2012) by incorporating explicitly the effect of grain boundaries on the plastic slip evolution. Within the framework of continuum thermodynamics, a consistent extension of the model is presented and a potential type non-...
A statistical approach to sparse multi-scale phase-based stereo
Ulusoy, İlkay (Elsevier BV, 2007-09-01)
In this study, a multi-scale phase based sparse disparity algorithm and a probabilistic model for matching uncertain phase are proposed. The features used are oriented edges extracted using steerable filters. Feature correspondences are estimated using phase-similarity at multiple scale using a magnitude weighting scheme. In order to achieve sub-pixel accuracy in disparity, we use a fine tuning procedure which employs the phase difference between corresponding feature points. We also derive a probabilistic ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
C. Aslan, A. Erdem, E. Erdem, and Z. S. Tarı, “Disconnected Skeleton: Shape at Its Absolute Scale,”
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, pp. 2188–2203, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/58038.