scholarly journals Review on Human face and Expression Recognition

2019 ◽  
Vol 3 (3) ◽  
pp. 31-40
Author(s):  
Dr.Dolly Reney .
Keyword(s):  
Face Recognition ◽  
Review Paper ◽  
Feature Representation ◽  
Expression Recognition ◽  
Human Face ◽  
Advantages And Disadvantages ◽  
Methods And Techniques ◽  
Input Source ◽  
Novel Approaches ◽  
The Voice

There are the different popular algorithms and techniques available which are used for implementation of face and expression recognition all having respective advantages and disadvantages. Some of the algorithms improve the efficiency of face and expression recognition, under the different varying illumination and expression conditions for input source. The main steps for face recognition are Feature representation and classification. The different authors have described different novel approaches for face and emotion recognition. Present review paper discrebie the different methods and techniques used to identified the person with the facial expression and person emotion with the voice of the person.

Image Classification Using Deep Neural Networks

2021 ◽  
pp. 75-85
Author(s):  
Sukanta Ghosh ◽  
Amar Singh
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Human Face ◽  
Emotion Detection ◽  
Face Location ◽  
Unique Item ◽  
High Level ◽  
Facial Images

Facial expression recognition is an activity that is performed by every human in their day-to-day lives. Each one of us analyses the expressions of the individuals we interact with to understand how people interact and respond with us. The malicious intentions of a thief or a person to be interviewed can be recognized with the help of his facial features and gestures. Face recognition from picture or video is a well-known point in biometrics inquiry. Numerous open places, for the most part, have reconnaissance cameras, and these cameras have their noteworthy security incentives. It is generally recognized that face recognition has assumed a significant job in reconnaissance framework. The genuine favorable circumstances of face-based distinguishing proof over different biometrics are uniqueness. Since the human face is a unique item having a high level of inconstancy in its appearance, face location is a troublesome issue in computer vision. This chapter explores emotion detection using facial images.

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

The Adaboost Algorithm Applied in ATM Automatic Identification System

2013 ◽  
Vol 753-755 ◽  
pp. 2941-2944
Author(s):  
Ming Hui Zhang ◽  
Yao Yu Zhang
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Computing Time ◽  
Automatic Identification ◽  
Identification System ◽  
Human Face ◽  
Detection Experiment ◽  
Adaboost Algorithm ◽  
Face Features ◽  
Human Faces

Seeing that human face features are unique, an increasing number of face recognition algorithms on existing ATM are proposed. Since face detection is a primary link of face recognition, our system adopts AdaBoost algorithm which is based on face detection. Experiment results demonstrated that the computing time of face detection using this algorithm is about 70ms, and the single and multiple human faces can be effectively measured under well environment, which meets the demand of the system.

Development of an algorithm for human face recognition

2021 ◽  
Author(s):  
Yuri Lipin ◽  
Sergey Storozhev ◽  
Ian Iakubchik
Keyword(s):  
Face Recognition ◽  
Human Face ◽  
Human Face Recognition
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