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Distance-based Global Descriptors for Multi-view Object Recognition

Published online by Cambridge University Press:  26 April 2019

Prasanna Kannappan  and
Herbert G. Tanner
Prasanna Kannappan
Affiliation:
Department of Mechanical Engineering, University of Delaware, Newark, DE, 19716, USA E-mail: prasanna@udel.edu
Herbert G. Tanner*
Affiliation:
Department of Mechanical Engineering, University of Delaware, Newark, DE, 19716, USA E-mail: prasanna@udel.edu
*
*Corresponding author. E-mail: btanner@udel.edu
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Summary

The paper reports on a new multi-view algorithm that combines information from multiple images of a single target object, captured at different distances, to determine the identity of an object. Due to the use of global feature descriptors, the method does not involve image segmentation. The performance of the algorithm has been evaluated on a binary classification problem for a data set consisting of a series of underwater images.

Keywords

Computer visionAutonomous underwater vehiclesMobile robotsAutomationNovel applications of robotics
Type
Articles
Information
Robotica , Volume 38 , Issue 1 , January 2020 , pp. 106 - 117
Copyright
© Cambridge University Press 2019 

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