Feature-based tracking on a multi-omnidirectional camera dataset

Banş Evrim Demiröz, Ismail Ari, Orhan Eroǧlu, Albert Ali Salah, Laie Akarun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

44 Scopus citations

Abstract

Omnidirectional cameras have a lot of potential for surveillance and ambient intelligence applications, since they provide increased coverage with fewer cameras. We introduce the new BOMNI dataset, collected with two omnidirectional cameras simultaneously. The dataset contains single subject and multi-subject interaction scenarios, as well as actions relevant for ambient assisted living, such as falling down. We describe evaluation protocols on this dataset, and provide benchmarking baseline results for two tracking systems based on bounding box and interest point matching after foreground-background segmentation, respectively.

Original languageEnglish
Title of host publication5th International Symposium on Communications Control and Signal Processing, ISCCSP 2012
DOIs
StatePublished - 2012
Event5th International Symposium on Communications Control and Signal Processing, ISCCSP 2012 - Rome, Italy
Duration: May 2 2012May 4 2012

Publication series

Name5th International Symposium on Communications Control and Signal Processing, ISCCSP 2012

Conference

Conference5th International Symposium on Communications Control and Signal Processing, ISCCSP 2012
Country/TerritoryItaly
CityRome
Period05/2/1205/4/12

Keywords

  • AAL dataset
  • Image sequence analysis
  • Object tracking
  • Omnidirectional cameras
  • Video surveillance

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