ICDAR2017 Robust Reading Challenge on Omnidirectional Video
| 言語 | 英語 |
|---|---|
| 種類 | 国際会議等の予稿 |
| 著者 | Masakazu Iwamura，Naoyuki Morimoto，Keishi Tainaka，Dena Bazazian，Lluis Gomez，Dimosthenis Karatzas |
| 論文名 | ICDAR2017 Robust Reading Challenge on Omnidirectional Video |
| 論文誌名 | Proc. 14th IAPR International Conference on Document Analysis and Recognition (ICDAR2017) |
| ページ | pp.1448-1453 |
| 発表場所 | Kyoto, Japan |
| 査読の有無 | 有 |
| 年月 | 2017年9月 |
| 分野 | パターン認識 |
| DOI | 10.1109/ICDAR.2017.236 |
| URL | http://rrc.cvc.uab.es/?ch=7 |
| キー | Iwamura2017_ICDAR (id=1599) |
要約
Results of ICDAR 2017 Robust Reading Challenge on Omnidirectional Video are presented. This competition uses Downtown Osaka Scene Text (DOST) Dataset that was captured in Osaka, Japan with an omnidirectional camera. Hence, it consists of sequential images (videos) of different view angles. Regarding the sequential images as videos (video mode), two tasks of localisation and end-to-end recognition are prepared. Regarding them as a set of still images (still image mode), three tasks of localisation, cropped word recognition and end-to-end recognition are prepared. As the dataset has been captured in Japan, the dataset contains Japanese text but also include text consisting of alphanumeric characters (Latin text). Hence, a submitted result for each task is evaluated in three ways: using Japanese only ground truth (GT), using Latin only GT and using combined GTs of both. Finally, by the submission deadline, we have received two submissions in the text localisation task of the still image mode. We intend to continue the competition in the open mode. Expecting further submissions, in this report we provide baseline results in all the tasks in addition to the submissions from the community.
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