Aaron Marburg
ABSTRACT
The estimation of the geometric relationship between pairs of images is a core task for many computer vision applications. Frequently, prior information on the inter-image or inter-camera geometry is available from e.g., a motion model or external sensors. When the images to be aligned show a planar scene, this prior geometry can be used to predict the locations of corresponding feature pairs. A number of algorithms are proposed for forming putative matches between sets of points features utilizing this geometric similarity in concert with the appearance similarity. The algorithms are evaluated over both similar and strongly dissimilar pairs of aerial photographs. Definition of an explicit search area given the estimated geometry provides the best results, although the failure mode given an erroneous prior is absolute.
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Index Terms
- Pose Guided Matching for Aerial Images
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