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Due to an iterative approach, intermediate results provide additional constraints such as coplanar boundary points over multiple shape primitives.
Shape boundaries are necessary for generating valid 3D models from multiple shape primitives, because shape primitives possibly have dimensions of infinite extent or they are only partially present in the scene.
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In this paper we present a method for clipping simple shape primitives at reasonable boundaries.
Hints for reasonable boundaries of shape primitives are indicated by different input sources and constraints.
Our approach generates structurally simple 3D models from shape primitives and point clouds.
The set of shape primitives is analyzed for constraints such as intersections.
Point clouds and range images provide information where shape primitives coincide with measured surface points.
Shape primitives are a valuable input for reconstructing 3D models from point clouds.
Traditional approaches used in building detection often rely on shape primitives that can be detected by 2D/3D computer vision techniques.
The shape primitives, e.g. planes or cylinders, are 2D manifolds which are automatically detected in unstructured point clouds.
We detect four types of structural cues, namely dominant mirror symmetries, rotational symmetries, shape primitives, and polylines capturing free-form shapes of the landmark not explained by symmetry.
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