3D indirect shape retrieval based on hand interaction

Irmak, Erdem Can
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 points are placed on the digital hand model and indicate whether the hand touches the 3D shape or not. In the second part, every 3D shape is represented by feeding hand features to the Support Vector Machine. Experiments validate that Support Vector Machine results are usable for retrieval of 3D shapes. Moreover, we compared the re- trieval performance of our method with an interaction based indirect method based on Data Glove as well as a direct method based on 3D shape distri- bution histograms. These comparison revealed different advantages of our method, which are i) being lower-cost compared to Data Glove, and ii) being more discriminative compared to a direct approach. The main contribution of this thesis is threefold: i) Noisy and/or deficient 3d shapes can be retrieved ii) The retrieval is not affected by the alignment of shape iii) Performance of the method is independent of the polygon count of the shape.


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 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 ...
Image-based extraction of material reflectance properties of a 3D rigid object
Erdem, ME; Erdem, IA; Yilmaz, UG; Atalay, Mehmet Volkan (2004-01-01)
In this study, an appearance reconstruction method based on extraction of material reflectance properties of a three-dimensional (3D) object from its two-dimensional (2D) images is explained. One of the main advantages of this system is that the reconstructed object can be rendered in real-time with photorealistic quality in varying illumination conditions. The reflectance of the object is decomposed into diffuse and specular components. While the diffuse component is stored in a global texture, the specula...
3D face recognition with local shape descriptors
İnan, Tolga; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2011)
This thesis represents two approaches for three dimensional face recognition. In the first approach, a generic face model is fitted to human face. Local shape descriptors are located on the nodes of generic model mesh. Discriminative local shape descriptors on the nodes are selected and fed as input into the face recognition system. In the second approach, local shape descriptors which are uniformly distributed across the face are calculated. Among the calculated shape descriptors that are discriminative fo...
3D Face Reconstruction Using Stereo Images and Structured Light
OZTURK, Ahmet Oguz; Halıcı, Uğur; ULUSOY PARNAS, İLKAY; AKAGUNDUZ, Erdem (2008-04-22)
In this paper, the 3D face scanner that we developed using stereo cameras and structured light together is presented. Structured light having a pattern of vertical lines is used to create feature points and to match them easily. 3D point cloud obtained by stereo analysis is post processed to obtain the 3D model in obj format.
Citation Formats
E. C. Irmak, “3D indirect shape retrieval based on hand interaction,” M.S. - Master of Science, Middle East Technical University, 2017.