Mobile visual object search and recognition

The proliferation of indoor positioning and navigation mobile applications based on various technologies, such as Wi-Fi access points, Bluetooth, Infrared, Radio Frequency Identification (RFID) and Near Field Communication (NFC) for indoor estimation positioning have already been implemented and are...

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Main Author: Wong, Li Yan
Other Authors: Yuan Junsong
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/67689
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-676892023-07-07T15:41:44Z Mobile visual object search and recognition Wong, Li Yan Yuan Junsong School of Electrical and Electronic Engineering Rapid-Rich Object Search (ROSE) Lab DRNTU::Engineering The proliferation of indoor positioning and navigation mobile applications based on various technologies, such as Wi-Fi access points, Bluetooth, Infrared, Radio Frequency Identification (RFID) and Near Field Communication (NFC) for indoor estimation positioning have already been implemented and are available on the market. In this project, we explore the feasibility of determining pedestrian’s location based on the images captured by a smart phone. Image Process/Retrieval API for Object Recognition would do the matching of captured image and retrieval of images in an offline database that is computed and stored in smart phone. The matching is done by features comparison between the captured image and database’s images. When there is a match between captured image and retrieval of images in database found, the captured image would do a lookup in an XML file to find a match between the name of database image and name of image stored in the XML file. Information such as name of place, floor, floor map and location would be returned with location marker identifying the pedestrian’s location on the 2-Dimensional floor map. Bachelor of Engineering 2016-05-19T04:50:46Z 2016-05-19T04:50:46Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67689 en Nanyang Technological University 87 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
Wong, Li Yan
Mobile visual object search and recognition
description The proliferation of indoor positioning and navigation mobile applications based on various technologies, such as Wi-Fi access points, Bluetooth, Infrared, Radio Frequency Identification (RFID) and Near Field Communication (NFC) for indoor estimation positioning have already been implemented and are available on the market. In this project, we explore the feasibility of determining pedestrian’s location based on the images captured by a smart phone. Image Process/Retrieval API for Object Recognition would do the matching of captured image and retrieval of images in an offline database that is computed and stored in smart phone. The matching is done by features comparison between the captured image and database’s images. When there is a match between captured image and retrieval of images in database found, the captured image would do a lookup in an XML file to find a match between the name of database image and name of image stored in the XML file. Information such as name of place, floor, floor map and location would be returned with location marker identifying the pedestrian’s location on the 2-Dimensional floor map.
author2 Yuan Junsong
author_facet Yuan Junsong
Wong, Li Yan
format Final Year Project
author Wong, Li Yan
author_sort Wong, Li Yan
title Mobile visual object search and recognition
title_short Mobile visual object search and recognition
title_full Mobile visual object search and recognition
title_fullStr Mobile visual object search and recognition
title_full_unstemmed Mobile visual object search and recognition
title_sort mobile visual object search and recognition
publishDate 2016
url http://hdl.handle.net/10356/67689
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