Cao, Yanpeng and McDonald, John
Viewpoint Invariant Features from Single Images Using 3D Geometry.
Applications of Computer Vision (WACV), 2009 Workshop on.
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
||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.
||feature extraction; geometry; image matching; image segmentation; Viewpoint Invariant Features; Single Images; 3D Geometry;
||Faculty of Science and Engineering > Computer Science
Dr Yanpeng Cao
||20 Jan 2011 15:46
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||Applications of Computer Vision (WACV), 2009 Workshop on
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