What does scene text tell us?

Seiichi Uchida, Yuto Shinahara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Scene text is one of the most important information sources for our daily life because it has particular functions such as disambiguation and navigation. In contrast, ordinary document text has no such function. Consequently, it is natural to have a hypothesis that scene text and document text have different characteristics. This paper tries to prove this hypothesis by semantic analysis of texts by word2vec, which is a neural network model to give a vector representation of each word. By the vector representation, we can have the semantic distributions of scene text and document text in Euclidean space and then determine their semantic categories by simple clustering. Experimental study reveals several differences between scene text and document text. For example, it is found that scene text is a semantic subset of document text and several semantic categories are very specific to scene text.

Original languageEnglish
Title of host publication2016 23rd International Conference on Pattern Recognition, ICPR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4047-4052
Number of pages6
ISBN (Electronic)9781509048472
DOIs
Publication statusPublished - Jan 1 2016
Event23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico
Duration: Dec 4 2016Dec 8 2016

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume0
ISSN (Print)1051-4651

Other

Other23rd International Conference on Pattern Recognition, ICPR 2016
CountryMexico
CityCancun
Period12/4/1612/8/16

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'What does scene text tell us?'. Together they form a unique fingerprint.

  • Cite this

    Uchida, S., & Shinahara, Y. (2016). What does scene text tell us? In 2016 23rd International Conference on Pattern Recognition, ICPR 2016 (pp. 4047-4052). [7900267] (Proceedings - International Conference on Pattern Recognition; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.2016.7900267