On human perception and automatic target recognition: Strategies for human-computer cooperation

David P. Williams, Michel Couillard, Samantha Dugelay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

This work addresses the task of underwater object recognition in sonar imagery when both human operators and automated algorithms are available. We discuss the issues that have impeded previous attempts at automation, raise key insights related to human perception, present strategies to exploit the skills of humans and computers synergistically, and demonstrate the utility of the proposed approaches on a real object-recognition task employing actual humans acting as operators. Importantly, the strategies outlined here can be immediately adopted in existing (unautomated) target recognition systems with minimal cost, effort, and risk, while still achieving potentially significant performance gains. Moreover, this progress lays the foundation for the acceptance of still-further automated systems in the future. Experimental results are provided from a real mine-search exercise at sea, with recognition performance as a function of human operator effort given for various human-computer divisions of labor.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4690-4695
Number of pages6
ISBN (Electronic)9781479952083
DOIs
StatePublished - Dec 4 2014
Event22nd International Conference on Pattern Recognition, ICPR 2014 - Stockholm, Sweden
Duration: Aug 24 2014Aug 28 2014

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other22nd International Conference on Pattern Recognition, ICPR 2014
Country/TerritorySweden
CityStockholm
Period8/24/148/28/14

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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