Groupwise registration of aerial images Arandjelovic, Ognjen, Pham, Duc-Son and Venkatesh, Svetha 2015, Groupwise registration of aerial images, in IJCAI 2015: Proceedings of the 24th International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, Palo Alto, Calif., pp. 2133-2139. Attached Files Name Description MIMEType Size Downloads Title Groupwise registration of aerial images Author(s) Arandjelovic, Ognjen Pham, Duc-Son Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Conference name International Joint Conference on Artificial Intelligence (24th : 2015 : Buenos Aires, Argentina) Conference location Buenos Aires, Argentina Conference dates 25-31 Jul. 2015 Title of proceedings IJCAI 2015: Proceedings of the 24th International Joint Conference on Artificial Intelligence Editor(s) Yang, Qiang Wooldridge, Michael Publication date 2015 Start page 2133 End page 2139 Total pages 7 Publisher International Joint Conferences on Artificial Intelligence Place of publication Palo Alto, Calif. Summary This paper addresses the task of time separated aerial image registration. The ability to solve this problem accurately and reliably is important for a variety of subsequent image understanding applications. The principal challenge lies in the extent and nature of transient appearance variation that a land area can undergo, such as that caused by the change in illumination conditions, seasonal variations, or the occlusion by non-persistent objects (people, cars). Our work introduces several novelties: (i) unlike all previous work on aerial image registration, we approach the problem using a set-based paradigm; (ii) we show how local, pairwise constraints can be used to enforce a globally good registration using a constraints graph structure; (iii) we show how a simple holistic representation derived from raw aerial images can be used as a basic building block of the constraints graph in a manner which achieves both high registration accuracy and speed. We demonstrate: (i) that the proposed method outperforms the state-of-the-art for pair-wise registration already, achieving greater accuracy and reliability, while at the same time reducing the computational cost of the task; and (ii) that the increase in the number of available images in a set consistently reduces the average registration error. ISBN 9781577357384 ISSN 1045-0823 Language eng Field of Research 080109 Pattern Recognition and Data Mining Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1 Full written paper - refereed ERA Research output type E Conference publication Copyright notice ©2015, International Joint Conferences on Artificial Intelligence Persistent URL http://hdl.handle.net/10536/DRO/DU:30082742 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Centre for Pattern Recognition and Data Analytics (PRADA) 2018 ERA Submission Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 11 Apr 2016, 14:12:34 EST Tue, 12 Apr 2016, 05:01:01 EST Tue, 12 Apr 2016, 06:09:02 EST Tue, 12 Apr 2016, 10:55:34 EST Tue, 12 Apr 2016, 10:57:58 EST Wed, 07 Sep 2016, 11:22:02 EST Wed, 06 Dec 2017, 14:37:49 EST Wed, 06 Dec 2017, 14:39:23 EST Tue, 08 May 2018, 10:40:48 EST Sat, 29 Sep 2018, 02:30:27 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 417 Abstract Views, 5 File Downloads  -  Detailed Statistics Created: Mon, 11 Apr 2016, 14:12:34 EST

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