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Vol. 5, Special Issue, March 2009, pp.119-134

 

 

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Neural Gas and Growing Neural Gas Networks for Selective 3D Sensing: a Comparative Study

 

Ana-Maria CRETU, Pierre PAYEUR and Emil M. PETRIU

School of Information Technology and Engineering, University of Ottawa

800 King Edward, Ottawa, ON, Canada, K1N 6N5

Tel.: 613-562-5800

E-mail: acretu@site.uottawa.ca, ppayeur@site.uottawa.ca, petriu@site.uottawa.ca

 

 

Received: 30 January 2009   /Accepted: 20 February 2009   /Published: 23 March 2009

 

Abstract: This paper addresses the topic of intelligent sensing for advanced robotic applications. It is a continuation of our research in the realm of automatic selection of regions of observation for fixed and mobile sensors, directed at innovative approaches to collect only relevant measurements without human guidance. The growing neural gas network solution proposed here for adaptively selecting regions of interest for additional sampling from a cloud of sparsely collected 3D measurements provides several advantages over the previous neural gas solution in terms of user intervention, size of resulting scan and training time. Experimental results and a comparative analysis are presented in the context of selective vision sampling.

 

Keywords: Selective sensing, 3D vision, Neural gas network, Growing neural gas network, Feature detection.

 

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