Design of an unmanned aerial vehicle 1

This report presents the design and implementation of an unmanned aerial vehicle (UAV) that is enhanced with reconnaissance and surveillance capabilities. The main focus of the report will be on human detection, this will be achieved by the use of a miniature computer installed on-board the UAV. Th...

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Main Author: Fun, Joel Bo Wen
Other Authors: Cheng Tee Hiang
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/67861
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-678612023-07-07T16:06:19Z Design of an unmanned aerial vehicle 1 Fun, Joel Bo Wen Cheng Tee Hiang School of Electrical and Electronic Engineering DRNTU::Engineering This report presents the design and implementation of an unmanned aerial vehicle (UAV) that is enhanced with reconnaissance and surveillance capabilities. The main focus of the report will be on human detection, this will be achieved by the use of a miniature computer installed on-board the UAV. There are many methods to achieve human detection, such as with the use of pyroelectric infrared sensors. However, in recent years, the field of computer vision has made significant progress, thus this report will explore human detection using research in computer vision. The implementation of the human detection was done using the Histogram of Oriented Gradient (HOG) feature descriptor. It works on the principle that an image will be partitioned into smaller segments know as a cell, and these cells are represented by a ‘star’ that shows the strength of the edge orientations. Together, these cells form a histogram of gradient directions. A Support Vector Machine (SVM) uses these histograms for classification with the aid of a sliding window detector. In addition, a second method of human detection using haar-like features will also be explored. Methods to reduce the load imposed on the central processing unit (CPU) were also explored, such as increasing the step size of the detection window as well as reducing the amount of processing that had to be done by the CPU. In doing so, detection accuracy decreases, thus optimization was done in an attempt to improve performance while not affecting detection accuracy to a large extent. Bachelor of Engineering 2016-05-23T04:19:47Z 2016-05-23T04:19:47Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67861 en Nanyang Technological University 77 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
spellingShingle DRNTU::Engineering
Fun, Joel Bo Wen
Design of an unmanned aerial vehicle 1
description This report presents the design and implementation of an unmanned aerial vehicle (UAV) that is enhanced with reconnaissance and surveillance capabilities. The main focus of the report will be on human detection, this will be achieved by the use of a miniature computer installed on-board the UAV. There are many methods to achieve human detection, such as with the use of pyroelectric infrared sensors. However, in recent years, the field of computer vision has made significant progress, thus this report will explore human detection using research in computer vision. The implementation of the human detection was done using the Histogram of Oriented Gradient (HOG) feature descriptor. It works on the principle that an image will be partitioned into smaller segments know as a cell, and these cells are represented by a ‘star’ that shows the strength of the edge orientations. Together, these cells form a histogram of gradient directions. A Support Vector Machine (SVM) uses these histograms for classification with the aid of a sliding window detector. In addition, a second method of human detection using haar-like features will also be explored. Methods to reduce the load imposed on the central processing unit (CPU) were also explored, such as increasing the step size of the detection window as well as reducing the amount of processing that had to be done by the CPU. In doing so, detection accuracy decreases, thus optimization was done in an attempt to improve performance while not affecting detection accuracy to a large extent.
author2 Cheng Tee Hiang
author_facet Cheng Tee Hiang
Fun, Joel Bo Wen
format Final Year Project
author Fun, Joel Bo Wen
author_sort Fun, Joel Bo Wen
title Design of an unmanned aerial vehicle 1
title_short Design of an unmanned aerial vehicle 1
title_full Design of an unmanned aerial vehicle 1
title_fullStr Design of an unmanned aerial vehicle 1
title_full_unstemmed Design of an unmanned aerial vehicle 1
title_sort design of an unmanned aerial vehicle 1
publishDate 2016
url http://hdl.handle.net/10356/67861
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