Login | Signup now       

Guest

 Click to see how  

HOME | VIDEOS | DOCUMENTS | COLLECTIONS | UPLOAD | BROADCAST | MY ACCOUNT | FEEDBACK | ABOUT

 

Share  Title: Gender Classification Using Support Vector Machines (SVMs)

 

 
Abstract

 Download Papers  Read full document

 
 
 
iConnect (Beta)   |   Sponsor  |   Comment   |    Report    Like    
 
 

Automatic face recognition is a classic problem in the area of computer vision research. This problem is still a very active area of research in vision community. The primary reason for this problem to get so much attention is the fact that face recognition finds application in many commercial applications and can work as a biometric in many law enforcement applications. The problem of Automatic face recognition can be formally defined as follows: Given a set of representative training images for each person in the database, determine the identity of a new face images from the stored data. There have been several techniques proposed in literature to extract different type of features related to shape, color, etc. of the face. Some of the techniques simply use the image pixel values as the features and reduce the dimension of these features by applying some constraints such that classification property of training image is preserved. In Project 1 of this course, we examined different kind of feature reduction method and used nearest neighbor approach as the classifier. The fundamental problem with the use of nearest neighbored approach as classifier is that the probability of error is quite high (twice as compared with Bayes classification). Hence, we explore another classifier known as Support Vector Machines (SVMs) which has gained significant attention in recent years. To test the performance of SVMs, we have reformulated the problem of face recognition into a gender classification problem. The problem can be stated as follows: given a test image, determine its gender.

 
 
Download Papers  Read full document
 
 
 
Most Viewed This Month
Supersonic Nozzle design by Method of Characteristics
A report discussing critical factors affecting Project performance
JPEG Progressive mode vs Sequential mode
Rayleigh criteria and Combustion Instability
Business Plan for Online Money Transfer
Adaptive Equalization Techniques using Least Mean Square (LMS) algorithm
Girlkultur Mass Culture in Weimar Germany
Adaptive Equalization Techniques using Recursive Least Square (RLS) algorithm
Combustion Instability in Liquid Rocket Engines
A Technical Essay on the Gyroplane
Laminar Separation Bubble
Experimental Study of Compressible Pipe Flow with Friction and Heat Addition
The Role of Density Gradient in Liquid Rocket Engine Combustion Instability
NOTAR Helicopter
Blind De-convolution of BPSK and QPSK modulated signal using Constant Modulus Algorithm (CMA).
 
Related Documents
Gender Classification Using Support Vector Machines (SVMs)
A Machine Learning approach to localization in Wireless Sensor Networks
Complex Classification Using Advanced Machine Learning Techniques
The Combustion of Aluminum in Solid Rocket Propellants
Hints for understanding low speed wind tunnels
Primitivism in Paul Gauguin's Where Do We Come From? What Are We? Where Are We Going? (1898)
Computational Support for the Collaborative Design, Routing, and Manipulation of Cable Harnesses
 
Member Documents
Adaptive Equalization Techniques using Least Mean Square (LMS) algorithm
Adaptive Equalization Techniques using Recursive Least Square (RLS) algorithm
Blind De-convolution of BPSK and QPSK modulated signal using Constant Modulus Algorithm (CMA).
Digital Image Processing
JPEG Progressive mode vs Sequential mode
Evaluation of Phase & Magnitude based Features for Speaker Identification
A Comparative Study of Different Face Recognition Algorithms
Gender Classification Using Support Vector Machines (SVMs)
Evaluation of phase and magnitude based features for speaker identification
Evaluation of Feature Recombination Techniques for Speaker Identification
A Machine Learning approach to localization in Wireless Sensor Networks
Complex Classification Using Advanced Machine Learning Techniques
 

Keywords

vector  machines  gender  classification  
 
 
 About This Document
 
 Subject Computer Science
 Category Term Paper
 Views 3296
 Downloads 311
 Added 25-03-10
 Contributor   ravigarg
 Add to Favourites
 Report Abuse
 
 Related Videos
 See More

 RunTime  00:00:02
 Uploaded  19-10-07
 Views  3672
   
 Aerodynamics

 RunTime  00:24:08
 Uploaded  20-12-07
 Views  3820
   
 What is social anthropolo...

 RunTime  moderate
 Uploaded  10-09-10
 Views  3399
   
 Conversations with Histor...

 RunTime  00:05:52
 Uploaded  12-02-09
 Views  3530
   
 MathCad Demo

 RunTime  00:09:58
 Uploaded  30-04-08
 Views  3635
   
 The Elegant Universe : Ca...

 RunTime  00:10:31
 Uploaded  26-08-09
 Views  3246
   
 Interference

 RunTime  00:18:29
 Uploaded  25-06-10
 Views  4082
   
 How Airplanes Fly

 RunTime  moderate
 Uploaded  16-09-10
 Views  4358
   
 IBM Research Computationa...

 RunTime  00:00:02
 Uploaded  19-10-07
 Views  3312
   
 Waves in a Large Free Sph...

 RunTime  00:00:02
 Uploaded  23-10-07
 Views  4711
   
 How RSS Feeds Work

 RunTime  00:00:02
 Uploaded  18-10-07
 Views  4075
   
 Manipulating Animated Fun...

 RunTime  00:00:02
 Uploaded  28-10-07
 Views  4704
   
 Theory of Lift Generation...

 RunTime  00:02:39
 Uploaded  15-01-10
 Views  3679
   
 Kennedy Space Center STS ...

 RunTime  00:05:11
 Uploaded  13-01-10
 Views  3932
   
 Aeroelastic Tests of an E...

 RunTime  00:01:19
 Uploaded  09-12-07
 Views  3407
   
 Birth of the Universe

 RunTime  00:09:40
 Uploaded  20-12-07
 Views  3580
   
 UHN Finding the Answers: ...

 RunTime  00:31:19
 Uploaded  14-07-08
 Views  3869
   
 Manifold Microchannel Coo...

 RunTime  00:00:02
 Uploaded  10-11-07
 Views  3024
   
 Astronomy - Orion

 

 

Comments | Queries | Clarifications