Adaptive 3-D object recognition from multiple views

1992 ◽  
Vol 14 (2) ◽  
pp. 107-124 ◽  
Author(s):  
M. Seibert ◽  
A.M. Waxman
Author(s):  
David Singer ◽  
Dorian Rohner ◽  
Dominik Henrich

AbstractA complete object database containing a model (representing geometric and texture information) of every possible workpiece is a common necessity e.g. for different object recognition or task planning approaches. The generation of these models is often a tedious process. In this paper we present a fully automated approach to tackle this problem by generating complete workpiece models using a robotic manipulator. A workpiece is recorded by a depth sensor from multiple views for one side, then turned, and captured from the other side. The resulting point clouds are merged into one complete model. Additionally, we represent the information provided by the object’s texture using keypoints. We present a proof of concept and evaluate the precision of the final models. In the end we conclude the usefulness of our approach showing a precision of around 1 mm for the resulting models.


Author(s):  
Hwang-Soo Kim ◽  
R. Jain ◽  
R. Volz

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