Development of a real-time human-activity spotting system

Computer vision has brought about efficient human machine interaction and its area of research has been expanding. Human activity recognition is important in its application in surveillance systems, being able to effectively detect abnormal human motion through advanced recognition system. The obje...

Full description

Saved in:
Bibliographic Details
Main Author: Goh, Wan Hua
Other Authors: Chua Chin Seng
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/71305
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-71305
record_format dspace
spelling sg-ntu-dr.10356-713052023-07-07T16:34:56Z Development of a real-time human-activity spotting system Goh, Wan Hua Chua Chin Seng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Computer vision has brought about efficient human machine interaction and its area of research has been expanding. Human activity recognition is important in its application in surveillance systems, being able to effectively detect abnormal human motion through advanced recognition system. The objective of human activity recognition is to be able to recognize human motions and behaviour pattern in real-time. The aim is to be able to identify complex human activity so that it is able to replace humans in controlling surveillances system. It is complex to implement a real-time activity recognition system, therefore this project implemented a non-real time system to recognize human activity. Under controlled environments such as having a static background and an indoor testing implementation, we developed a human activity recognition system through combinations of methods such as active contour segmentation, capturing of human motion in MHI and performing LBP operation to conduct recognition. Finally, the performance of the system is thoroughly analyzed through the conduction of recognition test and rejection test. Bachelor of Engineering 2017-05-16T03:22:34Z 2017-05-16T03:22:34Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/71305 en Nanyang Technological University 44 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Goh, Wan Hua
Development of a real-time human-activity spotting system
description Computer vision has brought about efficient human machine interaction and its area of research has been expanding. Human activity recognition is important in its application in surveillance systems, being able to effectively detect abnormal human motion through advanced recognition system. The objective of human activity recognition is to be able to recognize human motions and behaviour pattern in real-time. The aim is to be able to identify complex human activity so that it is able to replace humans in controlling surveillances system. It is complex to implement a real-time activity recognition system, therefore this project implemented a non-real time system to recognize human activity. Under controlled environments such as having a static background and an indoor testing implementation, we developed a human activity recognition system through combinations of methods such as active contour segmentation, capturing of human motion in MHI and performing LBP operation to conduct recognition. Finally, the performance of the system is thoroughly analyzed through the conduction of recognition test and rejection test.
author2 Chua Chin Seng
author_facet Chua Chin Seng
Goh, Wan Hua
format Final Year Project
author Goh, Wan Hua
author_sort Goh, Wan Hua
title Development of a real-time human-activity spotting system
title_short Development of a real-time human-activity spotting system
title_full Development of a real-time human-activity spotting system
title_fullStr Development of a real-time human-activity spotting system
title_full_unstemmed Development of a real-time human-activity spotting system
title_sort development of a real-time human-activity spotting system
publishDate 2017
url http://hdl.handle.net/10356/71305
_version_ 1772827375266955264