scholarly journals An experimental study of four variants of pose clustering from dense range data

2011 ◽  
Vol 115 (10) ◽  
pp. 1427-1448 ◽  
Author(s):  
Ulrich Hillenbrand ◽  
Alexander Fuchs
Author(s):  
RICHARD J. CAMPBELL ◽  
PATRICK J. FLYNN

Model-Based 3D object recognition systems have a variety of potential applications, but widespread use of such systems has not occurred, due to a number of factors including the representational limitations of models. One historical limitation is the discriminatory representation of free-form objects. The system described in this paper recognizes free-form objects in dense range data acquired by a structured light rangefinder. Images and object models are represented as a network of salient segments which are then brought into correspondence until a reliable pose estimate is available. Experiments with a database of images and object models highlight the contributions of this system.


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