liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A thermal infrared dataset for evaluation of short-term tracking methods
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Termisk Systemteknik AB, Linköping, Sweden.ORCID iD: 0000-0002-6591-9400
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Termisk Systemteknik AB, Linköping, Sweden.ORCID iD: 0000-0002-6763-5487
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6096-3648
2015 (English)Conference paper, Oral presentation only (Other academic)
Abstract [en]

During recent years, thermal cameras have decreased in both size and cost while improving image quality. The area of use for such cameras has expanded with many exciting applications, many of which require tracking of objects. While being subject to extensive research in the visual domain, tracking in thermal imagery has historically been of interest mainly for military purposes. The available thermal infrared datasets for evaluating methods addressing these problems are few and the ones that do are not challenging enough for today’s tracking algorithms. Therefore, we hereby propose a thermal infrared dataset for evaluation of short-term tracking methods. The dataset consists of 20 sequences which have been collected from multiple sources and the data format used is in accordance with the Visual Object Tracking (VOT) Challenge.

Place, publisher, year, edition, pages
2015.
Series
Svenska sällskapet för automatiserad bildanalys (SSBA)
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-127541OAI: oai:DiVA.org:liu-127541DiVA: diva2:925818
Conference
Swedish Symposium on Image Analysis
Available from: 2016-05-03 Created: 2016-05-03 Last updated: 2016-06-10Bibliographically approved

Open Access in DiVA

fulltext(3348 kB)574 downloads
File information
File name FULLTEXT01.pdfFile size 3348 kBChecksum SHA-512
ab0d79d33397c1b647425db6b0508eafb7812ad646d7250917bcad42817df68d50641251ac80d738c60d3d9f21185c061c830af3c5a59ee187eb0e883f296134
Type fulltextMimetype application/pdf

Authority records BETA

Berg, AmandaAhlberg, JörgenFelsberg, Michael

Search in DiVA

By author/editor
Berg, AmandaAhlberg, JörgenFelsberg, Michael
By organisation
Computer VisionFaculty of Science & Engineering
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 574 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 390 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf