Using Robust Regression to Find Font Usage Trends

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

抄録

Fonts have had trends throughout their history, not only in when they were invented but also in their usage and popularity. In this paper, we attempt to specifically find the trends in font usage using robust regression on a large collection of text images. We utilize movie posters as the source of fonts for this task because movie posters can represent time periods by using their release date. In addition, movie posters are documents that are carefully designed and represent a wide range of fonts. To understand the relationship between the fonts of movie posters and time, we use a regression Convolutional Neural Network (CNN) to estimate the release year of a movie using an isolated title text image. Due to the difficulty of the task, we propose to use of a hybrid training regimen that uses a combination of Mean Squared Error (MSE) and Tukey’s biweight loss. Furthermore, we perform a thorough analysis on the trends of fonts through time.

本文言語英語
ホスト出版物のタイトルDocument Analysis and Recognition – ICDAR 2021 Workshops - Proceedings
編集者Elisa H. Barney Smith, Umapada Pal
出版社Springer Science and Business Media Deutschland GmbH
ページ126-141
ページ数16
ISBN(印刷版)9783030861582
DOI
出版ステータス出版済み - 2021
イベントInternational Workshops co-located with the 16th International Conference on Document Analysis and Recognition, ICDAR 2021 - Lausanne, スイス
継続期間: 9月 5 20219月 10 2021

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12917 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議International Workshops co-located with the 16th International Conference on Document Analysis and Recognition, ICDAR 2021
国/地域スイス
CityLausanne
Period9/5/219/10/21

!!!All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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