3D Data Processing for Enhancement of Face Scanner Data

Date

2009-11-11

Author

BOZKURT, Nesli
Halıcı, Uğur
ULUSOY PARNAS, İLKAY
AKAGUNDUZ, Erdem

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

57
views

0
downloads

The data acquired by 3D face scanners have distortions such as spikes, holes and noise. Enhancement of 3D face data by removing these distortions while keeping the face features is important for the applications using these data. In this study, thresholding is used for removing spikes, thresholding together with face symmetry, is used for hole filling and bilateral filtering is used for smoothing and satisfactory results are obtained on FRGC 3D face data.

Subject Keywords

Recognition

URI

https://hdl.handle.net/11511/53554

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Face classification with support vector machine Kepenekci, B; Akar, Gözde (2004-04-30) A new approach to feature based frontal face recognition with Gabor wavelets and support vector machines is presented in this paper. The feature points are automatically extracted using the local characteristics of each individual face. A kernel that computes the similarity between two feature vectors, is used to map the face features to a space with higher dimension. To find the identity of a test face, the possible labels of each feature vector of that face is found with support vector machines, then the ...
3D object recognition from range images İzciler, Fatih; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2012) Recognizing generic objects by single or multi view range images is a contemporary popular problem in 3D object recognition area with developing technology of scanning devices such as laser range scanners. This problem is vital to current and future vision systems performing shape based matching and classification of the objects in an arbitrary scene. Despite improvements on scanners, there are still imperfections on range scans such as holes or unconnected parts on images. This studyobjects at proposing an...
A comparison on textured motion classification Oztekin, Kaan; Akar, Gözde (2006-01-01) Textured motion - generally known as dynamic or temporal texture analysis, classification, synthesis, segmentation and recognition is popular research areas in several fields such as computer vision, robotics, animation, multimedia databases etc. In the literature, several algorithms are proposed to characterize these textured motions such as stochastic and deterministic algorithms. However, there is no study which compares the performances of these algorithms. In this paper, we carry out a complete compari...
Investigation of Terrestrial Laser Scanning Reflectance Intensity and RGB Distributions to Assist Construction Material Identification Hassan, Muhammad Usman; Akçamete Güngör, Aslı; Akgül, Çağla (2017-07-07) t: Terrestrial Laser Scanning (TLS) allows collection of dense 3D point cloud data that captures a structure's as-is conditions. The geometric information from the collected data could be used to generate a 3D-model of the structure. However, the generated model usually lacks functional information - a basic requirement for a semantically rich information model. Some of the functional information (such as cost, mechanical and thermal performance) could be derived if the material used in a particular geometr...
Catadioptric hyperspectral imaging, an unmixing approach Baskurt, Didem Ozisik; BAŞTANLAR, YALIN; Çetin, Yasemin (Institution of Engineering and Technology (IET), 2020-10-01) Hyperspectral imaging systems provide dense spectral information on the scene under investigation by collecting data from a high number of contiguous bands of the electromagnetic spectrum. The low spatial resolutions of these sensors frequently give rise to the mixing problem in remote sensing applications. Several unmixing approaches are developed in order to handle the challenging mixing problem on perspective images. On the other hand, omnidirectional imaging systems provide a 360-degree field of view in...

Citation Formats

N. BOZKURT, U. Halıcı, İ. ULUSOY PARNAS, and E. AKAGUNDUZ, “3D Data Processing for Enhancement of Face Scanner Data,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53554.