Bridging text spotting and SLAM with junction features

Hsueh-Cheng Wang, Chelsea Finn, Liam Paull, Michael Kaess, Ruth Rosenholtz, Seth Teller, John Leonard

研究成果: Conference contribution同行評審

15 引文 斯高帕斯(Scopus)

摘要

Navigating in a previously unknown environment and recognizing naturally occurring text in a scene are two important autonomous capabilities that are typically treated as distinct. However, these two tasks are potentially complementary, (i) scene and pose priors can benefit text spotting, and (ii) the ability to identify and associate text features can benefit navigation accuracy through loop closures. Previous approaches to autonomous text spotting typically require significant training data and are too slow for real-time implementation. In this work, we propose a novel high-level feature descriptor, the 'junction', which is particularly well-suited to text representation and is also fast to compute. We show that we are able to improve SLAM through text spotting on datasets collected with a Google Tango, illustrating how location priors enable improved loop closure with text features.

原文English
主出版物標題IROS Hamburg 2015 - Conference Digest
主出版物子標題IEEE/RSJ International Conference on Intelligent Robots and Systems
發行者Institute of Electrical and Electronics Engineers Inc.
頁面3701-3708
頁數8
ISBN(電子)9781479999941
DOIs
出版狀態Published - 11 12月 2015
事件IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany
持續時間: 28 9月 20152 10月 2015

出版系列

名字IEEE International Conference on Intelligent Robots and Systems
2015-December
ISSN(列印)2153-0858
ISSN(電子)2153-0866

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015
國家/地區Germany
城市Hamburg
期間28/09/152/10/15

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