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BriefMatch: Dense binary feature matching for real-time optical flow estimation
Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-5698-5983
Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-7765-1747
2017 (engelsk)Inngår i: Proceedings of the Scandinavian Conference on Image Analysis (SCIA17) / [ed] Puneet Sharma, Filippo Maria Bianchi, Springer, 2017, Vol. 10269, s. 221-233Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Research in optical flow estimation has to a large extent focused on achieving the best possible quality with no regards to running time. Nevertheless, in a number of important applications the speed is crucial. To address this problem we present BriefMatch, a real-time optical flow method that is suitable for live applications. The method combines binary features with the search strategy from PatchMatch in order to efficiently find a dense correspondence field between images. We show that the BRIEF descriptor provides better candidates (less outlier-prone) in shorter time, when compared to direct pixel comparisons and the Census transform. This allows us to achieve high quality results from a simple filtering of the initially matched candidates. Currently, BriefMatch has the fastest running time on the Middlebury benchmark, while placing highest of all the methods that run in shorter than 0.5 seconds.

sted, utgiver, år, opplag, sider
Springer, 2017. Vol. 10269, s. 221-233
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349
Emneord [en]
computer vision, optical flow, feature matching, real-time computation
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-149418DOI: 10.1007/978-3-319-59126-1_19Scopus ID: 2-s2.0-85020383306ISBN: 978-3-319-59125-4 (tryckt)OAI: oai:DiVA.org:liu-149418DiVA, id: diva2:1228880
Konferanse
Scandinavian Conference on Image Analysis (SCIA17), Tromsø, Norway, 12-4 June, 2017
Tilgjengelig fra: 2018-06-28 Laget: 2018-06-28 Sist oppdatert: 2018-08-24bibliografisk kontrollert

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