Japanese / English

Detail of Publication

Text Language English
Authors Masakazu Iwamura, Takahiro Matsuda, Naoyuki Morimoto, Hitomi Sato, Yuki Ikeda and Koichi Kise
Title Downtown Osaka Scene Text Dataset
Journal Proc. 2nd International Workshop on Robust Reading (ECCV 2016 Workshops, Part I)
Vol. 9913
Series Lecture Notes in Computer Science (LNCS)
Pages pp.1-16
Publisher Springer
Location Amsterdam, Netherlands
Reviewed or not Reviewed
Presentation type Oral
Month & Year October 2016
Abstract This paper presents a new scene text dataset named Downtown Osaka Scene Text Dataset (in short, DOST dataset). The dataset consists of sequential images captured in shopping streets in downtown Osaka with an omnidirectional camera. Unlike most of existing datasets consisting of scene images intentionally captured, DOST dataset consists of uncontrolled scene images; use of an omnidirectional camera enabled us to capture videos (sequential images) of whole scenes surrounding the camera. Since the dataset preserved the real scenes containing texts as they were, in other words, they are scene texts in the wild. DOST dataset contained 32,147 manually ground truthed sequential images. They contained 935,601 text regions consisting of 797,919 legible and 137,682 illegible. The legible regions contained 2,808,340 characters. The dataset is evaluated using two existing scene text detection methods and one powerful commercial end-to-end scene text recognition method to know the difficulty and quality in comparison with existing datasets.
DOI 10.1007/978-3-319-46604-0_32
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