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Multi-View Object Instance Recognition in an Industrial Context

Mustafa, W, Pugeault, N, Buch, AG and Krüger, N (2015) Multi-View Object Instance Recognition in an Industrial Context Robotica, FirstV. pp. 1-22.

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Abstract

We present a fast object recognition system coding shape by viewpoint invariant geometric relations and appearance information. In our advanced industrial work-cell, the system can observe the work space of the robot by three pairs of Kinect and stereo cameras allowing for reliable and complete object information. From these sensors, we derive global viewpoint invariant shape features and robust color features making use of color normalization techniques. We show that in such a set-up, our system can achieve high performance already with a very low number of training samples, which is crucial for user acceptance and that the use of multiple views is crucial for performance. This indicates that our approach can be used in controlled but realistic industrial contexts that require—besides high reliability—fast processing and an intuitive and easy use at the end-user side.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Mustafa, WUNSPECIFIEDUNSPECIFIED
Pugeault, NUNSPECIFIEDUNSPECIFIED
Buch, AGUNSPECIFIEDUNSPECIFIED
Krüger, NUNSPECIFIEDUNSPECIFIED
Date : 1 July 2015
Identification Number : 10.1017/S0263574715000430
Additional Information : Copyright 2015 Cambridge University Press. Reprinted with permission.
Depositing User : Symplectic Elements
Date Deposited : 12 Aug 2015 10:42
Last Modified : 23 Dec 2015 02:08
URI: http://epubs.surrey.ac.uk/id/eprint/808141

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