Saliency-weighted holistic scene text recognition for unseen place categorization
An improvement in framework for unseen place categorization using scene text is proposed. Category score calculation using visual saliency weighting method is proposed to cope with problem of different importance of word locations on scene images. Additionally, a HOG feature extraction using sliding...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference Proceeding |
Published: |
2018
|
Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84904543396&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53421 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
id |
th-cmuir.6653943832-53421 |
---|---|
record_format |
dspace |
spelling |
th-cmuir.6653943832-534212018-09-04T09:48:57Z Saliency-weighted holistic scene text recognition for unseen place categorization Phawis Thammasorn Karn Patanukhom Rapeeporn Pimup Computer Science An improvement in framework for unseen place categorization using scene text is proposed. Category score calculation using visual saliency weighting method is proposed to cope with problem of different importance of word locations on scene images. Additionally, a HOG feature extraction using sliding window is proposed to obtain better holistic word recognition on scene images. As the result, the proposed method outperforms PHOG baseline in unseen place categorization with greater than 10 % improvement in the accuracy. © 2014 IEEE. 2018-09-04T09:48:57Z 2018-09-04T09:48:57Z 2014-01-01 Conference Proceeding 2-s2.0-84904543396 10.1109/JCSSE.2014.6841834 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84904543396&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53421 |
institution |
Chiang Mai University |
building |
Chiang Mai University Library |
country |
Thailand |
collection |
CMU Intellectual Repository |
topic |
Computer Science |
spellingShingle |
Computer Science Phawis Thammasorn Karn Patanukhom Rapeeporn Pimup Saliency-weighted holistic scene text recognition for unseen place categorization |
description |
An improvement in framework for unseen place categorization using scene text is proposed. Category score calculation using visual saliency weighting method is proposed to cope with problem of different importance of word locations on scene images. Additionally, a HOG feature extraction using sliding window is proposed to obtain better holistic word recognition on scene images. As the result, the proposed method outperforms PHOG baseline in unseen place categorization with greater than 10 % improvement in the accuracy. © 2014 IEEE. |
format |
Conference Proceeding |
author |
Phawis Thammasorn Karn Patanukhom Rapeeporn Pimup |
author_facet |
Phawis Thammasorn Karn Patanukhom Rapeeporn Pimup |
author_sort |
Phawis Thammasorn |
title |
Saliency-weighted holistic scene text recognition for unseen place categorization |
title_short |
Saliency-weighted holistic scene text recognition for unseen place categorization |
title_full |
Saliency-weighted holistic scene text recognition for unseen place categorization |
title_fullStr |
Saliency-weighted holistic scene text recognition for unseen place categorization |
title_full_unstemmed |
Saliency-weighted holistic scene text recognition for unseen place categorization |
title_sort |
saliency-weighted holistic scene text recognition for unseen place categorization |
publishDate |
2018 |
url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84904543396&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53421 |
_version_ |
1681424132118413312 |