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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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/10356/67689 |
| _version_ | 1811690803699908608 |
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| author | Wong, Li Yan |
| author2 | Yuan Junsong |
| author_facet | Yuan Junsong Wong, Li Yan |
| author_sort | Wong, Li Yan |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T06:09:48Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/67689 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:09:48Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | DRNTU::Engineering Wong, Li Yan Mobile visual object search and recognition |
| title | 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_short | Mobile visual object search and recognition |
| title_sort | mobile visual object search and recognition |
| topic | DRNTU::Engineering |
| url | http://hdl.handle.net/10356/67689 |
| work_keys_str_mv | AT wongliyan mobilevisualobjectsearchandrecognition |