Rapid facial recognition through wearable cameras

Face Recognition has been one of the most popular topics in the industry over the past decades. It is a biometric software that has many creative usages, for example, the camera of a smartphone where it will automatically focus on the face of the person and in China, cameras are used to capture the...

Full description

Saved in:
Bibliographic Details
Main Author: Sim, Jun Kai
Other Authors: Cham Tat Jen
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/137941
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-137941
record_format dspace
spelling sg-ntu-dr.10356-1379412020-04-20T04:53:40Z Rapid facial recognition through wearable cameras Sim, Jun Kai Cham Tat Jen School of Computer Science and Engineering astjcham@ntu.edu.sg Engineering::Computer science and engineering Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Face Recognition has been one of the most popular topics in the industry over the past decades. It is a biometric software that has many creative usages, for example, the camera of a smartphone where it will automatically focus on the face of the person and in China, cameras are used to capture the face of those people who jaywalk. The goal of this report is to present a face recognition system that makes use of k-Nearest Neighbors to achieve a rapid recognition of everyone that appears on the screen. Moreover, it can also be used as a memory aid for users. The report provides a detailed explanation of the software used, these include face recognition API, python libraries, pre-trained model and the reasons for choosing such techniques and methods to achieve the goals of the project. In addition, the flow chart and decision tree of the program will be used to provide a better illustration of how the face recognition system works. Lastly, the report has also stated further improvements which allow the whole face recognition project to achieve better user satisfaction and performance enhancement of the system. Bachelor of Engineering (Computer Science) 2020-04-20T04:53:40Z 2020-04-20T04:53:40Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/137941 en SCSE19-0352 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle Engineering::Computer science and engineering
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Sim, Jun Kai
Rapid facial recognition through wearable cameras
description Face Recognition has been one of the most popular topics in the industry over the past decades. It is a biometric software that has many creative usages, for example, the camera of a smartphone where it will automatically focus on the face of the person and in China, cameras are used to capture the face of those people who jaywalk. The goal of this report is to present a face recognition system that makes use of k-Nearest Neighbors to achieve a rapid recognition of everyone that appears on the screen. Moreover, it can also be used as a memory aid for users. The report provides a detailed explanation of the software used, these include face recognition API, python libraries, pre-trained model and the reasons for choosing such techniques and methods to achieve the goals of the project. In addition, the flow chart and decision tree of the program will be used to provide a better illustration of how the face recognition system works. Lastly, the report has also stated further improvements which allow the whole face recognition project to achieve better user satisfaction and performance enhancement of the system.
author2 Cham Tat Jen
author_facet Cham Tat Jen
Sim, Jun Kai
format Final Year Project
author Sim, Jun Kai
author_sort Sim, Jun Kai
title Rapid facial recognition through wearable cameras
title_short Rapid facial recognition through wearable cameras
title_full Rapid facial recognition through wearable cameras
title_fullStr Rapid facial recognition through wearable cameras
title_full_unstemmed Rapid facial recognition through wearable cameras
title_sort rapid facial recognition through wearable cameras
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/137941
_version_ 1681058417761845248