Robust behavior recognition in intelligent surveillance environments

Ganbayar Batchuluun, Yeong Gon Kim, Jong Hyun Kim, Hyung Gil Hong, Kang Ryoung Park

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Intelligent surveillance systems have been studied by many researchers. These systems should be operated in both daytime and nighttime, but objects are invisible in images captured by visible light camera during the night. Therefore, near infrared (NIR) cameras, thermal cameras (based on medium-wavelength infrared (MWIR), and long-wavelength infrared (LWIR) light) have been considered for usage during the nighttime as an alternative. Due to the usage during both daytime and nighttime, and the limitation of requiring an additional NIR illuminator (which should illuminate a wide area over a great distance) for NIR cameras during the nighttime, a dual system of visible light and thermal cameras is used in our research, and we propose a new behavior recognition in intelligent surveillance environments. Twelve datasets were compiled by collecting data in various environments, and they were used to obtain experimental results. The recognition accuracy of our method was found to be 97.6%, thereby confirming the ability of our method to outperform previous methods.

Original languageEnglish
Article number1010
JournalSensors
Volume16
Issue number7
DOIs
StatePublished - 1 Jul 2016

Keywords

  • Behavior recognition
  • Intelligent surveillance system
  • Thermal camera
  • Visible light camera

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