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Gestalt Principles for Attention and Segmentation in Natural and Artificial Vision Systems
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. (Center for Autonomous Systems)
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. (Center for Autonomous Systems)
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. (Center for Autonomous Systems)ORCID iD: 0000-0003-2965-2953
2011 (English)In: Semantic Perception, Mapping and Exploration (SPME), ICRA 2011 Workshop, eSMCs , 2011Conference paper, Published paper (Refereed)
Abstract [en]

Gestalt psychology studies how the human visual system organizes the complex visual input into unitary elements. In this paper we show how the Gestalt principles for perceptual grouping and for figure-ground segregation can be used in computer vision. A number of studies will be shown that demonstrate the applicability of Gestalt principles for the prediction of human visual attention and for the automatic detection and segmentation of unknown objects by a robotic system.

Place, publisher, year, edition, pages
eSMCs , 2011.
Keyword [en]
Visual Attention, Object Detection, Object Segmentation, Gestalt
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-47167OAI: oai:DiVA.org:kth-47167DiVA: diva2:454636
Conference
ICRA 2011 Workshop on Semantic Perception, Mapping and Exploration (SPME), Shanghai, China
Projects
EU, FP7 project eSMCs, IST-FP7-IP-270212SSF CoSy
Funder
EU, FP7, Seventh Framework Programme, IST-FP7-IP-270212
Note
QC 20111115Available from: 2011-11-15 Created: 2011-11-07 Last updated: 2012-01-24Bibliographically approved

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kootstra11spme.pdf(3148 kB)1301 downloads
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Type fulltextMimetype application/pdf

Authority records BETA

Kragic, Danica

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Kootstra, GertBergström, NiklasKragic, Danica
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CiteExportLink to record
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Citation style
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Output format
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