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Unbounded Sparse Census Transform using Genetic Algorithm
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-3425-3837
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0001-7934-6917
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-5832-5452
2019 (engelsk)Inngår i: 2019 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), IEEE , 2019, s. 1616-1625Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The Census Transform (CT) is a well proven method for stereo vision that provides robust matching, with respect to object boundaries, outliers and radiometric distortion, at a low computational cost. Recent CT methods propose patterns for pixel comparison and sparsity, to increase matching accuracy and reduce resource requirements. However, these methods are bounded with respect to symmetry and/or edge length. In this paper, a Genetic algorithm (GA) is applied to find a new and powerful CT method. The proposed method, Genetic Algorithm Census Transform (GACT), is compared with the established CT methods, showing better results for benchmarking datasets. Additional experiments have been performed to study the search space and the correlation between training and evaluation data.

sted, utgiver, år, opplag, sider
IEEE , 2019. s. 1616-1625
Serie
IEEE Winter Conference on Applications of Computer Vision, ISSN 2472-6737
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-44332DOI: 10.1109/WACV.2019.00177ISI: 000469423400170ISBN: 978-1-7281-1975-5 (tryckt)OAI: oai:DiVA.org:mdh-44332DiVA, id: diva2:1327850
Konferanse
19th IEEE Winter Conference on Applications of Computer Vision (WACV), JAN 07-11, 2019, Waikoloa Village, HI
Tilgjengelig fra: 2019-06-20 Laget: 2019-06-20 Sist oppdatert: 2019-06-20bibliografisk kontrollert

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Ahlberg, CarlLeon, MiguelEkstrand, FredrikEkström, Mikael

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