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A hash table approach for large scaleperceptual anchoring
Örebro University, School of Science and Technology, Örebro University, Sweden. (AASS)
2013 (English)In: In proceeding of: IEEE SMC 2013, Manchester, UK, October 13-16, 2013., 2013Conference paper (Refereed)
Abstract [en]

Perceptual anchoring deals with the problem ofcreating and maintaining the connection between percepts andsymbols that refer to the same physical object. When approachinglong term use of an anchoring framework which must copewith large sets of data, it is challenging to both efficiently andaccurately anchor objects. An approach to address this problemis through visual perception and computationally efficient binaryvisual features. In this paper, we present a novel hash tablealgorithm derived from summarized binary visual features. Thisalgorithm is later contextualized in an anchoring framework.Advantages of the internal structure of proposed hash tables arepresented, as well as improvements through the use of hierarchiesstructured by semantic knowledge. Through evaluation on alarger set of data, we show that our approach is appropriate forefficient bottom-up anchoring, and performance-wise comparableto recently presented search tree algorithm.

Place, publisher, year, edition, pages
Keyword [en]
Perceptual anchoring, large scale efficient matching, hash table, binary visual features, semantic categorization
National Category
Computer Science
Research subject
Computer Science
URN: urn:nbn:se:oru:diva-32897OAI: diva2:682935
IEEE International Conference on Systems, Man and Cybernetics
Swedish Research Council, 2011-6104
Available from: 2013-12-31 Created: 2013-12-31 Last updated: 2014-01-31Bibliographically approved

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Persson, Andreas
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School of Science and Technology, Örebro University, Sweden
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