A robust image retrieval system for mobile guide applications
We describe the prototype of an image retrieval system used for mobile guide applications. It allows users to send image queries of urban scenes using camera phones. The system uses a database of views of scenes to determine the poses of query views provided by the users. Information is then mapped...
Saved in:
Main Authors: | , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/101712 http://hdl.handle.net/10220/16780 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-101712 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1017122020-05-28T07:18:55Z A robust image retrieval system for mobile guide applications Lee, Jimmy Addison Yow, Kin Choong Kumazawa, Itsuo School of Computer Engineering DRNTU::Engineering::Computer science and engineering We describe the prototype of an image retrieval system used for mobile guide applications. It allows users to send image queries of urban scenes using camera phones. The system uses a database of views of scenes to determine the poses of query views provided by the users. Information is then mapped onto the query views. Our approach is based on a fully affine invariant descriptor, coined PRIUS, which can identify corresponding building facades across widely separated views despite the highly repetitive nature of the man-made environments. The system is substantiated by experiments that show that our approach outperforms the state-of-the-art approaches such as SIFT (scale-invariant feature transform) and MSER (maximally stable external regions) in image retrieval. 2013-10-24T07:08:04Z 2019-12-06T20:43:09Z 2013-10-24T07:08:04Z 2019-12-06T20:43:09Z 2012 2012 Journal Article Lee, J. A., Yow, K.-C., & Kumazawa, I. (2012). A robust image retrieval system for mobile guide applications. International Journal of Intelligent Systems, 27(4), 301-316. 0884-8173 https://hdl.handle.net/10356/101712 http://hdl.handle.net/10220/16780 10.1002/int.21522 en International journal of intelligent systems |
institution |
Nanyang Technological University |
building |
NTU Library |
country |
Singapore |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Computer science and engineering |
spellingShingle |
DRNTU::Engineering::Computer science and engineering Lee, Jimmy Addison Yow, Kin Choong Kumazawa, Itsuo A robust image retrieval system for mobile guide applications |
description |
We describe the prototype of an image retrieval system used for mobile guide applications. It allows users to send image queries of urban scenes using camera phones. The system uses a database of views of scenes to determine the poses of query views provided by the users. Information is then mapped onto the query views. Our approach is based on a fully affine invariant descriptor, coined PRIUS, which can identify corresponding building facades across widely separated views despite the highly repetitive nature of the man-made environments. The system is substantiated by experiments that show that our approach outperforms the state-of-the-art approaches such as SIFT (scale-invariant feature transform) and MSER (maximally stable external regions) in image retrieval. |
author2 |
School of Computer Engineering |
author_facet |
School of Computer Engineering Lee, Jimmy Addison Yow, Kin Choong Kumazawa, Itsuo |
format |
Article |
author |
Lee, Jimmy Addison Yow, Kin Choong Kumazawa, Itsuo |
author_sort |
Lee, Jimmy Addison |
title |
A robust image retrieval system for mobile guide applications |
title_short |
A robust image retrieval system for mobile guide applications |
title_full |
A robust image retrieval system for mobile guide applications |
title_fullStr |
A robust image retrieval system for mobile guide applications |
title_full_unstemmed |
A robust image retrieval system for mobile guide applications |
title_sort |
robust image retrieval system for mobile guide applications |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/101712 http://hdl.handle.net/10220/16780 |
_version_ |
1681058522620493824 |