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Hierarchical grouping - the gestalt assessments method

 
: Michaelsen, Eckart; Arens, Michael

:
Volltext urn:nbn:de:0011-n-4734043 (501 KByte PDF)
MD5 Fingerprint: 83327c2a938ea6f86fcf630838f94621
Erstellt am: 14.11.2017


Institute of Electrical and Electronics Engineers -IEEE-:
ICCV 2017, IEEE International Conference on Computer Vision : Venice, Italy, October 22-29, 2017
Piscataway, NJ: IEEE, 2017
S.1710-1714
International Conference on Computer Vision (ICCV) <2017, Venice>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Abstract
Real images contain reflection symmetry and repetition in rows with high probability. I.e. certain parts can be mapped on other certain parts by the usual Gestalt laws and are repeated there with high similarity. Moreover, such mapping comes in nested hierarchies – e.g. a reflection Gestalt that is made of repetition friezes, whose parts are again reflection symmetric compositions. It is our intention to develop and test methods that may automatically find, parametrize, and assess such nested hierarchies. This can be explicitly modelled by continuous assessment functions. The recognition performance is raised utilizing additional features such as colors. This paper reports examples from the 2017 data set.

: http://publica.fraunhofer.de/dokumente/N-473404.html