Adapting Hausdorff Metrics to Face Detection Systems: A Scale-Normalized Hausdorff Distance Approach

2005 ◽  
pp. 76-86 ◽  
Author(s):  
Pablo Suau
Keyword(s):  
Face Detection ◽  
Hausdorff Distance ◽  
Detection Systems ◽  
Distance Approach

scholarly journals Face Detection: Mapping Human Performance

Perception ◽  
10.1068/p5007 ◽  
2003 ◽  
Vol 32 (8) ◽  
pp. 903-920 ◽  
Author(s):  
Michael B Lewis ◽  
Andrew J Edmonds
Keyword(s):  
Reaction Time ◽  
Face Detection ◽  
Human Performance ◽  
Limited Attention ◽  
Focused Attention ◽  
Deformable Template ◽  
Detection Systems ◽  
Face Experiment ◽  
Extensive Body ◽  
Inversion Effects

The recognition of faces has been the focus of an extensive body of research, whereas the preliminary and prerequisite task of detecting a face has received limited attention from psychologists. Four experiments are reported that address the question how we detect a face. Experiment 1 reveals that we use information from the scene to aid detection. In experiment 2 we investigated which features of a face speed the detection of faces. Experiment 3 revealed inversion effects and an interaction between the effects of blurring and reduction of contrast. In experiment 4 the sizes of effects of reversal of orientation, luminance, and hue were compared. Luminance was found to have the greatest effect on reaction time to detect faces. The results are interpreted as suggesting that face detection proceeds by a pre-attentive stage that identifies possible face regions, which is followed by a focused-attention stage that employs a deformable template. Comparisons are drawn with automatic face-detection systems.

scholarly journals Security Implementation by Machine Learning Based Face Recognization with SVM

2021 ◽  
pp. 214-218
Author(s):  
Apurva Yawalikar ◽  
U. W. Hore
Keyword(s):  
Machine Learning ◽  
Face Recognition ◽  
Face Detection ◽  
Detection System ◽  
Object Class ◽  
Detection Systems ◽  
The Face ◽  
Object Class Detection ◽  
Human Faces ◽  
Work Done

Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given. As per the various face detection system seen various work done onto the detection with various way. In existing this are get evaluate with the HOG with SVM, which will help us to get the exact value so that it is necessary to implement the system which will more effective and advance. As per the face detection seen there are various face detection systems are implemented. Determining face is easy but recognition is quite typical so that we are proposed machine learning based face recognition with SVM which helps to determine and detect the faces So the proposed system will get integrated with highly efficient and effective SVM model for face recognition. The proposed methodology will help us to implement the face based security implementation in any security system like door lock, mobile screen lock etc.

A framework for design and validation of face detection systems

2017 ◽  
Author(s):  
Nelson C. S. Campos ◽  
Heron A. Monteiro ◽  
Alisson V. Brito ◽  
Antonio M. N. Lima ◽  
Elmar U. K. Melcher ◽  
...  
Keyword(s):  
Face Detection ◽  
Detection Systems

scholarly journals Face Detection and Processing: a Survey

2018 ◽  
Vol 7 (4.19) ◽  
pp. 1066
Author(s):  
R. P.Dahake ◽  
M. U. Kharat
Keyword(s):  
Real Time ◽  
Face Detection ◽  
Detection System ◽  
Research Work ◽  
Processing Unit ◽  
Detection Systems ◽  
Haar Feature ◽  
The Face ◽  
Feature Based ◽  
Graphical Processing

In the recent era facial image processing is gaining more importance and the face detection from image or from video have  number of applications  which are video surveillance, entertainment, security, multimedia, communication, Ubiquitous computing etc. Various research work are carried out for  face detection and processing which includes detection, tracking of the face, estimation of pose, clustering the detected faces etc. Although significant advances have been made, the performance of face detection systems provide satisfactory under controlled environment & may get degraded with some challenging scenario such as in real time video face detection and processing. There are many real-time applications where human face serves as identity and these application are time bound so time for detection of face from image or video and the further processing is very essential, thus here our goal is to discuss the face detection system overview and to review various human skin colors based approaches and Haar feature based approach for better detection performance. Detected faces tagging and clustering is essential in some cases, so for such further processing time factor plays important role. Some of the recent approaches to improve detection speed such as using Graphical Processing Unit are discussed and providing future directions in this area. 

scholarly journals Security Implementation by Machine Learning Based Face Recognization with SVM

2021 ◽  
pp. 409-416
Author(s):  
Apurva Yawalikar ◽  
Prof. U. W. Hore
Keyword(s):  
Machine Learning ◽  
Face Recognition ◽  
Face Detection ◽  
Detection System ◽  
Object Class ◽  
Detection Systems ◽  
The Face ◽  
Object Class Detection ◽  
Human Faces ◽  
Work Done

Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given. As per the various face detection system seen various work done onto the detection with various way. In existing this are get evaluate with the HOG with SVM, which will help us to get the exact value so that it is necessary to implement the system which will more effective and advance. As per the face detection seen there are various face detection systems are implemented. Determining face is easy but recognition is quite typical so that we are proposed machine learning based face recognition with SVM which helps to determine and detect the faces So the proposed system will get integrated with highly efficient and effective SVM model for face recognition. The proposed methodology will help us to implement the face based security implementation in any security system like door lock, mobile screen lock etc.

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