Abstract
The automation of imagery analysis processes leads to the need to detect change between pairs of aerial reconnaissance images. Ap- proximate camera models are available for these images, accurate up to a translation, and these are augmented with further constraints relat- ing to the task of monitoring vehicles. Horizontal, bilateral, Euclidean symmetry is used as a generic object model by which segmented curves are grouped, first in a 2-d approximation, and then in 3-d, resulting in a sparse 3-d Euclidean reconstruction of a symmetric object from a single view. The method is applied to sample images of parked aircraft.
This work was supported by DARPA contract F33615-94-C-1021, monitored by Wright Patterson Airforce Base, Dayton, OH. The views and conclusions contained in this document are those of the authors and should not be interpreted as repre- senting the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency, the United States Government, or General Electric.
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Curwen, R.W., Mundy, J.L. (1999). Constrained Symmetry for Change Detection. In: Shape, Contour and Grouping in Computer Vision. Lecture Notes in Computer Science, vol 1681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46805-6_11
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DOI: https://doi.org/10.1007/3-540-46805-6_11
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