scholarly journals Intelligent face recognition system based on OpenMV

2021 ◽  
Vol 2137 (1) ◽  
pp. 012074
Author(s):  
Yinxin Yan ◽  
Houcheng Yang ◽  
Zhangsi Yu ◽  
Ning Zhang
Keyword(s):  
Face Recognition ◽  
Online Shopping ◽  
Rapid Development ◽  
Recognition System ◽  
Internet Technology ◽  
Single Chip ◽  
Single Chip Microcomputer ◽  
The Core ◽  
Face Recognition System ◽  
Express Information

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.

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
Keyword(s):  
Face Recognition ◽  
Rapid Development ◽  
Recognition System ◽  
Video Stream ◽  
The Core ◽  
Face Recognition System ◽  
Depth Study ◽  
The Face

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.

The Application of Face Recognition Based on OpenCV

2011 ◽  
Vol 403-408 ◽  
pp. 2350-2353
Author(s):  
Su Li
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Recognition System ◽  
Biometric Recognition ◽  
The Core ◽  
Face Recognition System ◽  
Learning Functions ◽  
Key Technologies ◽  
Pca Algorithm ◽  
Mathematical Operations

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.

scholarly journals Design of face recognition system based on CNN

2020 ◽  
Vol 1601 ◽  
pp. 052011
Author(s):  
Yong Li ◽  
Zhe Wang ◽  
Yang Li ◽  
Xu Zhao ◽  
Hanwen Huang
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Face Recognition System

HUMAN FACE RECOGNITION FROM A SINGLE FRONT VIEW

1992 ◽  
Vol 06 (04) ◽  
pp. 571-593 ◽  
Author(s):  
CHING-WEN CHEN ◽  
CHUNG-LIN HUANG
Keyword(s):  
Face Recognition ◽  
Active Contour Model ◽  
Facial Feature ◽  
Recognition System ◽  
Facial Features ◽  
Human Face Recognition ◽  
Front View ◽  
Deformable Template ◽  
Face Recognition System ◽  
Feature Values

This paper presents a face recognition system which can identify the unknown identity effectively using the front-view facial features. In front-view facial feature extractions, we can capture the contours of eyes and mouth by the deformable template model because of their analytically describable shapes. However, the shapes of eyebrows, nostrils and face are difficult to model using a deformable template. We extract them by using the active contour model (snake). After the contours of all facial features have been captured, we calculate effective feature values from these extracted contours and construct databases for unknown identities classification. In the database generation phase, 12 models are photographed, and feature vectors are calculated for each portrait. In the identification phase if any one of these 12 persons has his picture taken again, the system can recognize his identity.

scholarly journals Face Recognition System for Set-Top Box-Based Intelligent TV

Sensors ◽  
2014 ◽  
Vol 14 (11) ◽  
pp. 21726-21749 ◽  
Author(s):  
Won Lee ◽  
Yeong Kim ◽  
Hyung Hong ◽  
Kang Park
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Set Top Box ◽  
Face Recognition System
Sign in / Sign up

Export Citation Format

Share Document