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    Viewpoint Invariant Features from Single Images Using 3D Geometry


    Cao, Yanpeng and McDonald, John (2009) Viewpoint Invariant Features from Single Images Using 3D Geometry. Applications of Computer Vision (WACV), 2009 Workshop on. pp. 1-6. ISSN 1550-5790

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    Abstract

    In this paper we present a novel approach for generating viewpoint invariant features from single images and demonstrate their application for robust matching over widely separated views. The key idea consists of retrieving building structure from single images and then utlising the recovered 3D geometry to improve the performances of feature extraction and matching. Urban environments usually contain many structured regularities, so that the images of those environments contain straight parallel lines and vanishing points, which can be efficiently exploited for 3D reconstruction. We present an effective scheme to recover 3D planar surfaces using the extracted line segments and their associated vanishing points. The viewpoint invariant features are then computed on the normalized front-parallel views of the obtained 3D planes. The advantages of the proposed approach include: (1) the new feature is very robust against perspective distortions and viewpoint changes due to its consideration of 3D geometry; (2) the features are completely computed from single images and do not need information from additional devices (e.g. stereo cameras, or active ranging devices). Experiments are carried out to demonstrate the proposed scheme ability to effectively handle very difficult wide baseline matching tasks in the presence of repetitive building structures and significant viewpoint changes.

    Item Type: Article
    Additional Information: Research presented in this paper was funded by a Strategic Research Cluster grant (07/SRC/I1168) by Science Foundation Ireland under the National Development Plan. The authors gratefully acknowledge this support.
    Keywords: feature extraction; geometry; image matching; image segmentation; Viewpoint Invariant Features; Single Images; 3D Geometry;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 2398
    Identification Number: https://doi.org/10.1109/WACV.2009.5403061
    Depositing User: Dr Yanpeng Cao
    Date Deposited: 20 Jan 2011 15:46
    Journal or Publication Title: Applications of Computer Vision (WACV), 2009 Workshop on
    Publisher: IEEE
    Refereed: Yes
    Funders: Science Foundation Ireland
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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