his.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
An Efficient Way to Estimate the Focus of Expansion
School of Computer Science, Nanjing University of Posts and Telecommunications Nanjing City, China.
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och automatiseringsteknik, Production and Automation Engineering)
2018 (engelsk)Inngår i: 2018 3rd IEEE International Conference on Image, Vision and Computing (ICIVC 2018), IEEE, 2018, s. 691-695Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Detecting independent motion from a single camera is a difficult task in computer vision. It is because the captured image sequences are the combinations of the objects' movements and the camera's ego-motion. One major branch is to find the focus of expansion (FOE) instead as the goal. This is ideal for the situation commonly seen in UAV's camera system. In this case, the translation is dominant in camera's motion while the rotation is relatively small. To separate the ego motion and scene structure, many researchers used the directional flow as the theoretic basis and extracted its properties related to FOE. In this paper, we formulate finding FOE as an optimizing problem. The position of FOE has the minimal standard deviation for the directional flow in all directions, which is also subjected to the introduced constraint. The experiments show the proposed methods out-perform the previous method.

sted, utgiver, år, opplag, sider
IEEE, 2018. s. 691-695
Emneord [en]
focus of expansion, directional flow, independent motion detection
HSV kategori
Forskningsprogram
Produktion och automatiseringsteknik; INF201 Virtual Production Development
Identifikatorer
URN: urn:nbn:se:his:diva-16399DOI: 10.1109/ICIVC.2018.8492881ISI: 000448170000136Scopus ID: 2-s2.0-85056554769ISBN: 978-1-5386-4992-3 (tryckt)ISBN: 978-1-5386-4991-6 (digital)ISBN: 978-1-5386-4990-9 (digital)OAI: oai:DiVA.org:his-16399DiVA, id: diva2:1263338
Konferanse
2018 3rd IEEE International Conference on Image, Vision and Computing (ICIVC 2018), Chongqing, China, June 27-29, 2018
Tilgjengelig fra: 2018-11-15 Laget: 2018-11-15 Sist oppdatert: 2019-02-05bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Personposter BETA

Ericson, Stefan

Søk i DiVA

Av forfatter/redaktør
Ericson, Stefan
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 153 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf