Implementation of a Face Recognition System Based on the Video Stream

2014 ◽  
Vol 602-605 ◽  
pp. 1602-1605
Author(s):  
Yong Hua Yin ◽  
Quan Yin Zhu ◽  
Yun Yang Yan

Nowadays, face recognition has the rapid development with more in-depth study and more achievements. Many achievements have been applied in different fields which improves that the study of face recognition is valuable and meaningful. In this paper, a face recognition system based on the video stream is implemented. And the face recognition system consists of the following modules: face adding module, face recognition module, information querying module and global settings module. Among the all modules, face recognition modules is the core of the whole system in which completes the most of the work of the whole system. In practice, the results of the system are valuable and the system is able to meet the requirements of some applications.

2021 ◽  
Vol 2137 (1) ◽  
pp. 012074
Author(s):  
Yinxin Yan ◽  
Houcheng Yang ◽  
Zhangsi Yu ◽  
Ning Zhang

Abstract With the rapid development of e-commerce in Internet technology, online shopping has become the mainstream shopping method accepted and favored by people. E-commerce and online shopping not only bring convenience to people’s life, but also aggravate the surge of express delivery. In order to improve the pick-up efficiency, this paper designs an intelligent pick-up express system based on OpenMV face recognition. The system takes STM32 single chip microcomputer as the core controller, and reads and transmits express information based on OpenMV face recognition; The trolley tracks and avoids obstacles independently, and takes parts according to the planned path of the system. Experiments show that the system can realize express automatic pick-up, and has a broad application prospect.


2014 ◽  
Vol 971-973 ◽  
pp. 1710-1713
Author(s):  
Wen Huan Wu ◽  
Ying Jun Zhao ◽  
Yong Fei Che

Face detection is the key point in automatic face recognition system. This paper introduces the face detection algorithm with a cascade of Adaboost classifiers and how to configure OpenCV in MCVS. Using OpenCV realized the face detection. And a detailed analysis of the face detection results is presented. Through experiment, we found that the method used in this article has a high accuracy rate and better real-time.


Now a days one of the critical factors that affects the recognition performance of any face recognition system is partial occlusion. The paper addresses face recognition in the presence of sunglasses and scarf occlusion. The face recognition approach that we proposed, detects the face region that is not occluded and then uses this region to obtain the face recognition. To segment the occluded and non-occluded parts, adaptive Fuzzy C-Means Clustering is used and for recognition Minimum Cost Sub-Block Matching Distance(MCSBMD) are used. The input face image is divided in to number of sub blocks and each block is checked if occlusion present or not and only from non-occluded blocks MWLBP features are extracted and are used for classification. Experiment results shows our method is giving promising results when compared to the other conventional techniques.


Author(s):  
Dr.C K Gomathy ◽  
T. suneel ◽  
Y.Jeeevan Kumar Reddy

The Face recognition and image or video recognition are popular research topics in biometric technology. Real-time face recognition is an exciting field and a rapidly evolving issue. Key component analysis (PCA) may be a statistical technique collectively called correlational analysis . The goal of PCA is to scale back the massive amount of knowledge storage to the dimensions of the functional space required to render the face recognition system. The wide one-dimensional pixel vector generated from the two-dimensional image of the face and therefore the basic elements of the spatial function are designed for face recognition using PCA. this is often the projection of your own space. Sufficient space is decided by the brand. specialise in the eigenvectors of the covariance matrix of the fingerprint image collection. i'm building a camera-based real-time face recognition system and installing an algorithm. Use OpenCV, Haar Cascade, Eigen face, Fisher Face, LBPH and Python for program development.


2012 ◽  
Vol 241-244 ◽  
pp. 1705-1709
Author(s):  
Ching Tang Hsieh ◽  
Chia Shing Hu

In this paper, a robust and efficient face recognition system based on luminance distribution by using maximum likelihood estimation is proposed. The distribution of luminance components of the face region is acquired and applied to maximum likelihood test for face matching. The experimental results showed that the proposed method has a high recognition rate and requires less computation time.


2004 ◽  
Vol 13 (05) ◽  
pp. 1133-1146
Author(s):  
H. OTHMAN ◽  
T. ABOULNASR

In this paper, the effect of mixture tying on a second-order 2D Hidden Markov Model (HMM) is studied as applied to the face recognition problem. While tying HMM parameters is a well-known solution in the case of insufficient training data that leads to nonrobust estimation, it is used here to improve the overall performance in the small model case where the resolution in the observation space is the main problem. The fully-tied-mixture 2D HMM-based face recognition system is applied to the facial database of AT&T and the facial database of Georgia Institute of Technology. The performance of the proposed 2D HMM tied-mixture system is studied and the expected improvement is confirmed.


Author(s):  
Noradila Nordin ◽  
Nurul Husna Mohd Fauzi

Attendance marking in a classroom is one of the methods used to track the student’s presence in the lecture. The conventional method that is being enforced has shown to be vulnerable, inaccurate and time-consuming especially in a large classroom. It is difficult to identify absentees and proxy attendees based on the conventional attendance marking method. In order to overcome the challenges faced in the conventional method, a web-based mobile attendance system with facial recognition feature is proposed. It incorporated the existing mobile devices with a camera and the face recognition system to allow the attendance system to be used in classrooms automatically and efficiently with minor implementation requirements. The system prototype received positive responses from the volunteers who tested the system to replace the conventional attendance marking.


2011 ◽  
Vol 403-408 ◽  
pp. 2350-2353
Author(s):  
Su Li

Face recognition is a significant method, which is one of the biometric recognition. A face recognition system consists of two key technologies, namely, face detection and face recognition. In order to achieve two key technologies, Haar-Like feature and AdsBoost algorithm can be used to achieve face detection module. And PCA algorithm can be used to achieve face recognition module. For achieve application more quickly and efficiently, the core of the system develops with OpenCV. And the main use is its image processing, mathematical operations, and machine learning functions.


2019 ◽  
Vol 8 (1) ◽  
pp. 239-245 ◽  
Author(s):  
Shamsul J. Elias ◽  
Shahirah Mohamed Hatim ◽  
Nur Anisah Hassan ◽  
Lily Marlia Abd Latif ◽  
R. Badlishah Ahmad ◽  
...  

Attendance is important for university students. However, generic way of taking attendance in universities may include various problems. Hence, a face recognition system for attendance taking is one way to combat the problem. This paper will present an automated system that will automatically saves student’s attendance into the database using face recognition method. The paper will elaborate on student attendance system, image processing, face detection and face recognition. The face detection part will be done by using viola-jones algorithm method while the face recognition part will be carried on by using local binary pattern (LBP) method. The system will ensure that the attendance taking process will be faster and more accurate.


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