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
Analysis of Face Recognition Algorithms for Online and Automatic Annotation of Personal Videos
Date
2010-05-08
Author
Yılmaztürk, Mehmet
Ulusoy Parnas, İlkay
Çiçekli, Fehime Nihan
Metadata
Show full item record
Item Usage Stats
239
views
0
downloads
Cite This
Different from previous automatic but offline annotation systems, this paper studies automatic and online face annotation for personal videos/episodes of TV series considering Nearest Neighbourhood, LDA and SVM classification with Local Binary Patterns, Discrete Cosine Transform and Histogram of Oriented Gradients feature extraction methods in terms of their recognition accuracies and execution times. The best performing feature extraction method and the classifier pair is found out to be SVM classification with Discrete Cosine Transform features
Subject Keywords
Facial Feature Extraction
,
Classification
,
Support Vector Machines with Multiple Kernels
URI
0
https://hdl.handle.net/11511/84754
DOI
https://doi.org/10.1007/978-90-481-9794-1_45
Conference Name
25th international symposium on computer and information sciences (22–24 Eylül 2010)
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Synthesis of past time signal temporal logic formulas using monotonicity properties
Ergürtuna, Mert.; Aydın Göl, Ebru; Department of Computer Engineering (2020)
Due to its expressivity and efficient algorithms, Signal Temporal Logic (STL) is widely used in runtime verification, formal control and analysis of time series data. While it is relatively easy to define an STL formula, simulate the system and mark the unexpected behaviors according to the formula as in the testing process, finding an STL formula that would detect the underlying cause of the errors is a complicated process. The main motivation of this thesis is to find a method that would explain the event...
MODELLING OF KERNEL MACHINES BY INFINITE AND SEMI-INFINITE PROGRAMMING
Ozogur-Akyuz, S.; Weber, Gerhard Wilhelm (2009-06-03)
In Machine Learning (ML) algorithms, one of the crucial issues is the representation of the data. As the data become heterogeneous and large-scale, single kernel methods become insufficient to classify nonlinear data. The finite combinations of kernels are limited up to a finite choice. In order to overcome this discrepancy, we propose a novel method of "infinite" kernel combinations for learning problems with the help of infinite and semi-infinite programming regarding all elements in kernel space. Looking...
Performance Comparison of Different Sparse Array Configurations for Ultra-Wideband, Near-field Imaging Applications
Cetin, Beyzat Talat; Alatan, Lale (2017-03-24)
The aim of this study is to compare the performance of different multiple-input multiple-output (MIMO) array topologies, intended to be used in ultra-wideband (UWB) near-field imaging applications, by using an analysis method that does not include the effects of image reconstruction algorithm. For this purpose, maximum projection method, previously proposed for the analysis of UWB arrays under far-field conditions, is utilized and modified to obtain two way beam patterns of UWB arrays operating in the near-...
Evaluation of classical and sparsity-based methods for parametric recovery problems
Başkaya, Hasan Can; Öktem, Figen S..; Department of Electrical and Electronics Engineering (2020)
Parametric reconstruction problems arise in many areas such as array processing, wireless communication, source separation, and spectroscopy. In a parametric recovery problem, the unknown model parameters in each superimposed signal are estimated from noisy observations. Classical methods perform the recovery over directly on the continuous-valued parameter space by solving a nonlinear inverse problem. Recently sparsity-based methods have also been applied to parametric recovery problems. These methods disc...
Real-Time Detection of Interharmonics and Harmonics of AC Electric Arc Furnaces on GPU Framework
Uz-Logoglu, Eda; Salor, Ozgul; Ermiş, Muammer (2019-11-01)
In this paper, a method based on the multiple synchronous reference frame analysis is recommended and implemented to detect time-varying harmonics and interharmonics of rapidly fluctuating asymmetrical industrial loads. The experimental work has been carried out on a typical three-phase alternating current arc furnace installation. In the recommended method, the reference frame is rotated in both directions at speeds corresponding to the positive and negative sequences of all harmonics and all interharmonic...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Yılmaztürk, İ. Ulusoy Parnas, and F. N. Çiçekli, “Analysis of Face Recognition Algorithms for Online and Automatic Annotation of Personal Videos,” London, UK, 2010, vol. 62, p. 231, Accessed: 00, 2021. [Online]. Available: 0.