1 February 1991 Scene description: an iterative approach
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Proceedings Volume 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods; (1991); doi: 10.1117/12.25225
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Analyzing sensor data to describe the shape of unknown three-dimensional objects randomly jumbled together is an area of great research interest. It is encountered in a large variety of industrial tasks of the bin-picking type. Classical approaches to bin-picking use strong object models. However a priori models are not available in many unstructured material handling applications such as mailpiece singulation random or mixed part feeding scavenging and other similar tasks. In such applications the key vision problem is determining how the partially visible objects relate to each other and to other invisible objects that may be underneath. The shapes of the partially visible objects are constrained by the invisible contacts between the objects the forces such as friction and gravity acting at these contacts and the assumed solidity (impenetrability) of the objects. This paper shows how heuristics such as object symmetry and assumptions such as general viewpoint can be used to generate initial hypotheses about the shapes of partially visible objects. These hypotheses are then iteratively expanded to determine the possible extents ofthe objects using criteria such as coplanarity ofdisconnected surfaces and intersection of swept volumes. A detailed example that illustrates the methods is described. 1. 0
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Prasanna G. Mulgaonkar, Jeff L. DeCurtins, Cregg K. Cowan, "Scene description: an iterative approach", Proc. SPIE 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods, (1 February 1991); doi: 10.1117/12.25225; https://doi.org/10.1117/12.25225

3D modeling

Computer vision technology

Machine vision


Robot vision



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