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 indirect shape retrieval based on hand interaction
Date
2020-01-01
Author
Irmak, Erdem Can
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
192
views
0
downloads
Cite This
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 that SVM results are useful for retrieval of 3D shapes. We also compare the retrieval performance of our method with an interaction-based indirect method based on the Data Glove controller as well as a direct method based on 3D shape distribution histograms. These comparisons reveal different advantages of our method, which are (i) being lower-cost and more accurate compared to the Data Glove, and (ii) being more discriminative compared to a direct approach. We finally note that our algorithm is rigid-motion invariant and able to explore databases of arbitrarily represented 3D shapes.
Subject Keywords
Software
,
Computer Vision and Pattern Recognition
,
Computer Graphics and Computer-Aided Design
URI
https://hdl.handle.net/11511/39696
Journal
VISUAL COMPUTER
DOI
https://doi.org/10.1007/s00371-018-1597-4
Collections
Department of Computer Engineering, Article
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...
MARS - A TOOL-BASED MODELING, ANIMATION, AND PARALLEL RENDERING SYSTEM
AKTIHANOGLU, M; OZGUC, B; AYKANAT, C (Springer Science and Business Media LLC, 1994-01-01)
This paper describes a system for modeling, animating, previewing and rendering articulated objects. The system has a modeler of objects that consists of joints and segments. The animator interactively positions the articulated object in its stick, control vertex, or rectangular prism representation and previews the motion in real time. Then the data representing the motion and the models is sent to a multicomputer [iPSC/2 Hypercube (Intel)]. The frames are rendered in parallel, exploiting the coherence bet...
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 object recognition using scale space of curvatures
Akagündüz, Erdem; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2011)
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 ...
Automatic reconstruction of broken 3-D surface objects
Üçoluk, Göktürk; Toroslu, İsmail Hakkı (Elsevier BV, 1999-08-01)
The problem of reconstruction of broken surface objects embedded in 3-D space is handled. A coordinate independent representation for the crack curves is developed. A new robust matching algorithm is proposed which serves for finding matching pieces even when some brittle pieces are missing. A prototype system having an X-based GUI has been developed. This system generates artifical wire-frame data of broken pieces (with some noise) for a pot-shaped 3-D object and then recombines it using the proposed algor...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. C. Irmak and Y. Sahillioğlu, “3D indirect shape retrieval based on hand interaction,”
VISUAL COMPUTER
, pp. 5–17, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39696.