How features of the human face affect recognition: a statistical comparison of three face recognition algorithms

Author(s):  
G. Givens ◽  
J.R. Beveridge ◽  
B.A. Draper ◽  
P. Grother ◽  
P.J. Phillips

Face recognition is a growing-up branch of pattern recognition in the context of image and vision. Conferences have arisen and brand new technologies have been coming to light providing more and more accurate recognition rates. But what is face recognition? The problem statement could be formulated this way: “Given still or video images of a scene, identify or verify one or more persons in the scene using a stored database of faces” [1]. Face recognition branch is core inasmuch the applications involving recognition algorithms for human face are aimed at different applications such as biometrics, authentication, identification of suspects. This chapter offers an overview of what are similarity and similarity measures.


Author(s):  
Sourabh Kumar ◽  
Bhaskar Kapoor Kapoor

Proposing a security system for surveillance of home alone children for safety purpose and send an alert to the register mobile number if some kind of intrusion is detected. I have used Viola-Jones algorithm to detect human face from the live camera and then frame is resized then resized image is processed by the Local Binary Pattern Histograms (LBPH) algorithm and save the model in a YML file and then it is implemented on live cam feed in which the algorithm will detect the face and if some unknown face has been identified it will trigger a notification to the registered mobile number using a python library named [Pywhatkit] so the user can perform security measures. Keywords: Face recognition, Open-CV, HAAR cascade, face recognition.


Author(s):  
WEI-LI FANG ◽  
YING-KUEI YANG ◽  
JUNG-KUEI PAN

Several 2DPCA-based face recognition algorithms have been proposed hoping to achieve the goal of improving recognition rate while mostly at the expense of computation cost. In this paper, an approach named SI2DPCA is proposed to not only reduce the computation cost but also increase recognition performance at the same time. The approach divides a whole face image into smaller sub-images to increase the weight of features for better feature extraction. Meanwhile, the computation cost that mainly comes from the heavy and complicated operations against matrices is reduced due to the smaller size of sub-images. The reduced amount of computation has been analyzed and the integrity of sub-images has been discussed thoroughly in the paper. The experiments have been conducted to make comparisons among several better-known approaches and SI2DPCA. The experimental results have demonstrated that the proposed approach works well on reaching the goals of reducing computation cost and improving recognition performance simultaneously.


Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P

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.


Sign in / Sign up

Export Citation Format

Share Document