Learning High-Level Visual Concepts Using Attributed Primitives and Genetic Programming

Krzysztof Krawiec

doi:10.1007/11732242_48

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Title

Learning High-Level Visual Concepts Using Attributed Primitives and Genetic Programming

Authors

Krzysztof Krawiec ^{[ 1 ][ P ]}

^{[ 1 ]} Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | ^{[ P ]} employee

Year of publication

2006

Chapter type

paper

Publication language

english

Abstract

EN In this paper, we present a novel approach to genetic learning of high-level visual concepts that works with sets of attributed visual primitives rather than with raster images. The paper presents the approach in detail and verifies it in an experiment concerning locating objects in real-world 3D scenes.

Pages (from - to)

515 - 519

DOI

10.1007/11732242_48

URL

https://link.springer.com/chapter/10.1007/11732242_48

Book

Applications of Evolutionary. Computing EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, Budapest, Hungary, April 10-12, 2006. Proceedings

Presented on

EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, 10-12.04.2006, Budapest, Hungary

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