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
3D object recognition using scale space of curvatures
Download
index.pdf
Date
2011
Author
Akagündüz, Erdem
Metadata
Show full item record
Item Usage Stats
190
views
76
downloads
Cite This
In this thesis, a generic, scale and resolution invariant method to extract 3D features from 3D surfaces, is proposed. Features are extracted with their scale (metric size and resolution) from range images using scale-space of 3D surface curvatures. Different from previous scale-space approaches; connected components within the classified curvature scale-space are extracted as features. Furthermore, scales of features are extracted invariant of the metric size or the sampling of the range images. Geometric hashing is used for object recognition where scaled, occluded and both scaled and occluded versions of range images from a 3D object database are tested. The experimental results under varying scale and occlusion are compared with SIFT in terms of recognition capabilities. In addition, to emphasize the importance of using scale space of curvatures, the comparative recognition results obtained with single scale features are also presented.
Subject Keywords
Computer input-output equipment.
,
Computer engineering.
,
Three-dimensional imaging.
URI
http://etd.lib.metu.edu.tr/upload/12612901/index.pdf
https://hdl.handle.net/11511/20745
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
3D indirect shape retrieval based on hand interaction
Irmak, Erdem Can; Sahillioğlu, Yusuf; Department of Game Technologies (2017)
In this thesis, a novel 3D indirect shape analysis method is presented which successfully retrieves 3D shapes based on the hand-object interaction. In the first part of the study, the human hand information is processed and trans- ferred to the virtual environment by Leap Motion Controller. Position and rotation of the hand, the angle of the finger joints are used for this part in our method. Also, in this approach, a new type of feature, which we call inter- action point, is introduced. These interaction p...
3d face representation and recognition using spherical harmonics
Tunçer, Fahri; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2008)
In this study, a 3D face representation and recognition method based on spherical harmonics expansion is proposed. The input data to the method is range image of the face. This data is called 2.5 dimensional. Input faces are manually marked on the two eyes, nose and chin points. In two dimensions, using the marker points, the human face is modeled as two concentric half ellipses for the selection of region of interest. These marker points are also used in three dimensions to register the faces so that the n...
3D indirect shape retrieval based on hand interaction
Irmak, Erdem Can; Sahillioğlu, Yusuf (Springer Science and Business Media LLC, 2020-01-01)
In this work, we present a novel 3D indirect shape analysis method which successfully retrieves 3D shapes based on hand-object interaction. To this end, the human hand information is first transferred to the virtual environment by the Leap Motion controller. Position-, angle- and intersection-based novel features of the hand and fingers are used for this part. In the guidance of these features that define the way humans grab objects, a support vector machine (SVM) classifier is trained. Experiments validate...
3D Object Recognition by Geometric Hashing
Eskizara, Omer; Akagündüz, Erdem; Ulusoy, İlkay (2009-01-01)
Using transform invariant 3D fatures obtained from a database of 3D range images, geometric hashing is applied for the purpose of 3D object recognition. Mean (H) and Gaussian (K) curvature values within a scale-space of the surface is used Since H and K values are used and a scale-space of the surface is constructed the method is independent of transformation and resolution. The method is tested on the Stuttgart 3D range image database [1].
Photometric stereo considering highlights and shadows
Büyükatalay, Soner; Halıcı, Uğur; Birgül, Özlem; Department of Electrical and Electronics Engineering (2011)
Three dimensional (3D) shape reconstruction that aims to reconstruct 3D surface of objects using acquired images, is one of the main problems in computer vision. There are many applications of 3D shape reconstruction, from satellite imaging to material sciences, considering a continent on earth or microscopic surface properties of a material. One of these applications is the automated firearm identification that is an old, yet an unsolved problem in forensic science. Firearm evidence matching algorithms rel...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. Akagündüz, “3D object recognition using scale space of curvatures,” Ph.D. - Doctoral Program, Middle East Technical University, 2011.