Abstract
An important computer vision task in robotics is modeling of 3D objects in a robot's workspace. This paper presents a method for generating octree models of 3D solid objects from their silhouettes obtained in a sequence of images. The silhouettes of objects which are projected into an image and the center of projection of the image generate 3D conic volumes. A 3D model of the objects is iteratively constructed by intersecting such conic volumes obtained from a sequence of images. Hierarchical octree structures are used to represent and to process 3D volume data efficiently. The volumes of individual objects are labeled by a connectivity-labeling algorithm, and surface-normal vectors are added to their surface volume elements. The volume of the workspace not yet seen in any image is also included in the model.
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