Location-aware mobile information hub

In recent years, 3G network has gain popularity which leads to increased consumerism in the area of smartphones. Smartphones allows the user to retrieve information anywhere as long it is connected to its subscriber. This promotes the habit for mobile user to retrieve information immediately when in...

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Main Author: Ng, Zhan Ke.
Other Authors: Chau Lap Pui
Format: Final Year Project
Language:English
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/10356/49688
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-496882023-07-07T16:40:05Z Location-aware mobile information hub Ng, Zhan Ke. Chau Lap Pui Yap Kim Hui School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing In recent years, 3G network has gain popularity which leads to increased consumerism in the area of smartphones. Smartphones allows the user to retrieve information anywhere as long it is connected to its subscriber. This promotes the habit for mobile user to retrieve information immediately when in doubt of something. This project aims to help mobile users retrieve landmark information through the capturing of images. Landmark image recognition has been around for some time but its development in the context of Singapore has been limited. In this project we will study the reasons of the image that will constitute to the overall accuracy of the system and the limitations of the database such as undesirable features. Undesirable features are unwanted features that are extracted from the image which deranges the focus of the image. Geometric Verification (GV) and saliency detection have been proposed to tackle these undesirable features. GV shows a slight improvement in terms of accuracy (1-2%) with a downside of large increase in recognition timing. Saliency detection on the other hand, presents a significant improvement in terms of accuracy (> 7%) with a compromising slight increase in the recognition time (~0.1s). Lastly, we study the impact of different image size used in feature extraction for evaluation of the system performance. Moving forward, we can explore on incorporating GPS information stored in the images to narrow the database for matching, thus increasing the speed of the system. Bachelor of Engineering 2012-05-23T04:08:34Z 2012-05-23T04:08:34Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/49688 en Nanyang Technological University 65 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::Computer hardware, software and systems
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Ng, Zhan Ke.
Location-aware mobile information hub
description In recent years, 3G network has gain popularity which leads to increased consumerism in the area of smartphones. Smartphones allows the user to retrieve information anywhere as long it is connected to its subscriber. This promotes the habit for mobile user to retrieve information immediately when in doubt of something. This project aims to help mobile users retrieve landmark information through the capturing of images. Landmark image recognition has been around for some time but its development in the context of Singapore has been limited. In this project we will study the reasons of the image that will constitute to the overall accuracy of the system and the limitations of the database such as undesirable features. Undesirable features are unwanted features that are extracted from the image which deranges the focus of the image. Geometric Verification (GV) and saliency detection have been proposed to tackle these undesirable features. GV shows a slight improvement in terms of accuracy (1-2%) with a downside of large increase in recognition timing. Saliency detection on the other hand, presents a significant improvement in terms of accuracy (> 7%) with a compromising slight increase in the recognition time (~0.1s). Lastly, we study the impact of different image size used in feature extraction for evaluation of the system performance. Moving forward, we can explore on incorporating GPS information stored in the images to narrow the database for matching, thus increasing the speed of the system.
author2 Chau Lap Pui
author_facet Chau Lap Pui
Ng, Zhan Ke.
format Final Year Project
author Ng, Zhan Ke.
author_sort Ng, Zhan Ke.
title Location-aware mobile information hub
title_short Location-aware mobile information hub
title_full Location-aware mobile information hub
title_fullStr Location-aware mobile information hub
title_full_unstemmed Location-aware mobile information hub
title_sort location-aware mobile information hub
publishDate 2012
url http://hdl.handle.net/10356/49688
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