Issue No. 04 - April (1989 vol. 11)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.19034
<p>A technique is presented for recognizing a 3D object (a model in an image library) from a single 2D silhouette using information such as corners (points with high positive curvatures) and occluding contours, rather than straight line segments. The silhouette is assumed to be a parallel projection of the object. Each model is stored as a set of the principal quadtrees, from which the volume/surface octree of the model is generated. Feature points (i.e. corners) are extracted to guide the recognition process. Four-point correspondences between the 2D feature points of the observed object and 3D feature points of each model are hypothesized, and then verified by applying a variety of constraints to their associated viewing parameters. The result of the hypothesis and verification process is further validated by 2D contour matching. This approach allows for a method of handling both planar and curved objects in a uniform manner, and provides a solution to the recognition of multiple objects with occlusion as demonstrated by the experimental results.</p>
picture processing; pattern recognition; shape recognition; occluding contours; 3D object; 2D silhouette; quadtrees; volume/surface octree; feature points; contour matching; pattern recognition; picture processing; trees (mathematics)
"Model Construction and Shape Recognition from Occluding Contours," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 11, no. , pp. 372-389, 1989.