Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Groupwise registration of aerial images

    Access Status
    Open access via publisher
    Authors
    Arandjelovic, O.
    Pham, DucSon
    Venkatesh, S.
    Date
    2015
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Arandjelovic, O. and Pham, D. and Venkatesh, S. 2015. Groupwise registration of aerial images, in Qiang Yang, Michael Wooldridge (ed), 24th International Conference on Artificial Intelligence, Jul 25 2015, pp. 2133-2139. Buenos Aires, Argentina: AAAI.
    Source Title
    Proceedings of the 24th International Conference on Artificial Intelligence
    Source Conference
    24th International Conference on Artificial Intelligence
    Additional URLs
    https://www.aaai.org/ocs/index.php/IJCAI/IJCAI15/paper/view/10802
    ISBN
    9781577357384
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/22175
    Collection
    • Curtin Research Publications
    Abstract

    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, pair-wise 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.

    Related items

    Showing items related by title, author, creator and subject.

    • Efficient and accurate set-based registration of time-separated aerial images
      Arandjelovic, O.; Pham, DucSon; Venkatesh, S. (2015)
      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 ...
    • Groupwise registration of aerial images
      Arandjelovic, O.; Pham, DucSon; Venkatesh, S. (2015)
      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 ...
    • Model-to-image registration and automatic texture mapping using a video sequence taken by a mini UAV
      Iwaszczuk, D.; Helmholz, Petra; Belton, David; Stilla, A. (2013)
      3D city models are used in many fields. Photorealistic building textures find applications such as façade reconstruction, thermal building inspections and heat leakage detection using thermal infrared (TIR) images, ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.