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Lahiru G. Jayatilaka

 

Publications by Lahiru G. Jayatilaka (bibliography)

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2011
 
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Jayatilaka, Lahiru G., Bertuccelli, Luca F., Staszewski, James and Gajos, Krzysztof Z. (2011): Evaluating a pattern-based visual support approach for humanitarian landmine clearance. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 453-462. Available online

Unexploded landmines have severe post-conflict humanitarian repercussions: landmines cost lives, limbs and land. For deminers engaged in humanitarian landmine clearance, metal detectors remain the primary detection tool as more sophisticated technologies fail to get adopted due to restrictive cost, low reliability, and limited robustness. Metal detectors are, however, of limited effectiveness, as modern landmines contain only minimal amounts of metal, making them difficult to distinguish from the ubiquitous but harmless metallic clutter littering post-combat areas. We seek to improve the safety and efficiency of the demining process by developing support tools that will enable deminers to make better decisions using feedback from existing metal detectors. To this end, in this paper we propose and evaluate a novel, pattern-based visual support approach inspired by the documented strategies employed by expert deminers. In our laboratory study, participants provided with a prototype of our support tool were 80% less likely to mistake a mine for harmless clutter. A follow-up study demonstrates the potential of our pattern-based approach to enable peer decision-making support during landmine clearance. Lastly, we identify several design opportunities for further improving deminers' decision making capabilities.

© All rights reserved Jayatilaka et al. and/or their publisher

2010
 
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Jayatilaka, Lahiru G., Bertuccelli, Luca F., Staszewski, James and Gajos, Krzysztof Z. (2010): PETALS: a visual interface for landmine detection. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 427-428. Available online

Post-conflict landmines have serious humanitarian repercussions: landmines cost lives, limbs and land. The primary method used to locate these buried devices relies on the inherently dangerous and difficult task of a human listening to audio feedback from a metal detector. Researchers have previously hypothesized that expert operators respond to these challenges by building mental patterns with metal detectors through the identification of object-dependent spatially distributed metallic fields. This paper presents the preliminary stages of a novel interface -- Pattern Enhancement Tool for Assisting Landmine Sensing (PETALS) -- that aims to assist with building and visualizing these patterns, rather than relying on memory alone. Simulated demining experiments show that the experimental interface decreases classification error from 23% to 5% and reduces localization error by 54%, demonstrating the potential for PETALS to improve novice deminer safety and efficiency.

© All rights reserved Jayatilaka et al. and/or their publisher

 
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