Abstract
We present two approaches for finding large man-made objects in outdoor scenes through the fusion of color and geometric information. We have tested our methods on images of concrete bridges. Both methods use a priori knowledge and models of bridges.
The first method has a 2-D model of a side view of the bridge. Rectangular features are extracted from the image. The corresponding surface material is estimated by a color matching algorithm. Next, an expert system uses Truth-Maintenance techniques to group features through the fusion of geometric relationships and color cues. It proposes hypotheses, and verifies them. Flexibility in the match allows for non-optimal conditions, such as oblique viewing angles (causing perspective distortion) or partial occlusions.
The other method consists of a 3-D hypothesized representation of the world, projected to 2-D for a tentative match with the image. The goals and issues are presented, and the proposed system architecture is described. Two completed subsystems for cue generation are shown: a vanishing point finder and a color-matcher.
This research was supported in part by ARO Contract DAAL03-87-K-0089.
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© 1993 Springer-Verlag Berlin Heidelberg
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Lebègue, X.F., Baker, D.C., Aggarwal, J.K. (1993). Fusion of Color and Geometric Information. In: Aggarwal, J.K. (eds) Multisensor Fusion for Computer Vision. NATO ASI Series, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-02957-2_13
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DOI: https://doi.org/10.1007/978-3-662-02957-2_13
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