Geometric feature based age classification using facial images

2012 ◽  
Author(s):  
S. Izadpanahi ◽  
O. Toygar
Keyword(s):  
Geometric Feature ◽  
Feature Based ◽  
Facial Images

HUMAN AGE CLASSIFICATION WITH OPTIMAL GEOMETRIC RATIOS AND WRINKLE ANALYSIS

2014 ◽  
Vol 28 (02) ◽  
pp. 1456003 ◽  
Author(s):  
SHIMA IZADPANAHI ◽  
ÖNSEN TOYGAR
Keyword(s):  
Feature Extraction ◽  
Age Groups ◽  
Research Network ◽  
Geometric Feature ◽  
Support Vector ◽  
Support Vector Classifier ◽  
Age Group Classification ◽  
Feature Based ◽  
Facial Anthropometry ◽  
Facial Images

This paper presents geometric feature-based model for age group classification of facial images. The feature extraction is performed considering significance of the effects that age has on facial anthropometry. Particle Swarm Optimization (PSO) technique is used to find optimized subset of geometric features. The relevance and importance of age differentiation capability of the features are evaluated using support vector classifier. The facial images are categorized in seven major age groups. The effectiveness and accuracy of the proposed feature extraction is demonstrated with the experiments that are conducted on two publicly available databases namely Face and Gesture Recognition Research Network (FGNET) Aging Database and Iranian Face Database (IFDB). The results demonstrate that the success rate of the classification is 92.62%. The results also show significant improvement compared to the state-of-the-art models.

Episodal associative memory approach for sequencing interactive features in process planning

1992 ◽  
Vol 6 (3) ◽  
pp. 177-197 ◽  
Author(s):  
Tim E. Westhoven ◽  
C. L. Philip Chen ◽  
Yoh-Han Pao ◽  
Steven R. LeClair
Keyword(s):  
Associative Memory ◽  
Process Planning ◽  
Geometric Feature ◽  
Neural Computing ◽  
Qualitative Information ◽  
Dynamic Memory ◽  
Feature Interactions ◽  
Solid Geometry ◽  
Feature Based ◽  
Interacting Features

Process planning is the function that converts an engineering design into a manufacturing plan. One of the problems in feature-based process planning is the sequencing of features. Features must be given an order for removal. This order, or sequence, is partially dependent on the geometric relationships between the features. If the geometric relationships between features are such that they dictate a particular sequence, the features are said to have an interaction. Identifying these interactions is an important first step in creating the process plan. An approach to solve this problem using constructive solid geometry operations and the Episodal Associative Memory (EAM) is demonstrated. The EAM is an associative memory that integrates dynamic memory organization and neural computing techniques. The geometric feature relationships can be represented by a pattern. This pattern captures very qualitative information about the geometric positions fo the features. The EAM can organize these patterns into groups of similar geometric relationships. A method for dealing with exceptions, and for retrieving and storing general machining problems associated with interacting features will be described. The system implemented is shown to correctly sequence several types of feature interactions.

Development of a Blade Parametric Modeling Methodology for Design and Analysis of Computer Experiments

2015 ◽  
Author(s):  
Zafer Leylek ◽  
A. J. Neely
Keyword(s):  
Physical Space ◽  
Computer Experiments ◽  
Parametric Modeling ◽  
Rotor Blades ◽  
Geometric Feature ◽  
Physical Parameters ◽  
Base Line ◽  
Turbine Stator ◽  
Modeling Methodology ◽  
Feature Based

This paper will present an enhanced parametric modeling technique for gas turbine stator and rotor blades. The enhanced blade parametric modeling system has been developed as part of a wider research program into global surrogate modeling of compressor and turbine aerodynamic performance using Design and Analysis of Computer Experiments (DACE) based techniques. The proposed method is based on a hybrid of geometric feature and Non-uniform Rational B-Spline (NURBS) based techniques. A base-line geometry is defined using the physical parameters and represented using NURBS curves and surfaces. A number of constraints are then imposed on the parametric model to ensure that DACE techniques can be effectively utilized. This is accomplished by mapping the geometric feature based parameters from the physical space to an alternative parametric space so that all feasible and numerically stable blade configurations can be represented using a unit hyper-cube. This method ensures a one-to-one mapping between the parametric sub-space and the geometric feature based system. The mapping is geometrically and numerically stable and does not produce ill-conditioned and unrealistic blade geometries. The development of the blade parametric modeling process allows the application of the complete suit of DACE tools and techniques. The method is valid for all axial blade profiles which include compressor and turbine stator and rotor blades.

Building geometric feature based maps for indoor service robots

2006 ◽  
Vol 54 (7) ◽  
pp. 546-558 ◽  
Author(s):  
Diego Rodriguez-Losada ◽  
Fernando Matia ◽  
Ramon Galan
Keyword(s):  
Service Robots ◽  
Geometric Feature ◽  
Feature Based

Congruence and geometric feature-based commutative encryption-watermarking method for vector maps

2021 ◽  
pp. 105009
Author(s):  
Na Ren ◽  
Deyu Tong ◽  
Hanchuan Cui ◽  
Changqing Zhu ◽  
Qifei Zhou
Keyword(s):  
Geometric Feature ◽  
Vector Maps ◽  
Feature Based

Automatic Processing System of Welding Spots in Auto-Body Welding Lines

2012 ◽  
Vol 472-475 ◽  
pp. 2993-2997
Author(s):  
Bin Zhu ◽  
Yan Tao Wang ◽  
Tao Yu
Keyword(s):  
Processing System ◽  
Automatic Processing ◽  
Geometric Feature ◽  
Commercial Software ◽  
Welding Spot ◽  
Welding Line ◽  
Feature Based ◽  
Auto Body ◽  
Solid Edge

Assigning welding spots to stations in the design of an auto-body welding line is a tedious job and error-prone. In this paper, an automatic processing system of welding spots has been implemented on the platforms of the commercial software, CATIA and Solid Edge. The geometric feature based technology is used to recognize welding spots automatically. The corresponding station is found for each welding spot according to the order of stations and the types of welding spots automatically. The system provides other convenient functions to facilitate the processing of welding spots as well. It has been used in the design of auto-body welding lines very successfully.

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