Environmentally robust motion detection for video surveillance

Hyenkyun Woo, Yoon Mo Jung, Jeong Gyoo Kim, Jin Keun Seo

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Most video surveillance systems require to manually set a motion detection sensitivity level to generate motion alarms. The performance of motion detection algorithms, embedded in closed circuit television (CCTV) camera and digital video recorder (DVR), usually depends upon the preselected motion sensitivity level, which is expected to work in all environmental conditions. Due to the preselected sensitivity level, false alarms and detection failures usually exist in video surveillance systems. The proposed motion detection model based upon variational energy provides a robust detection method at various illumination changes and noise levels of image sequences without tuning any parameter manually. We analyze the structure mathematically and demonstrate the effectiveness of the proposed model with numerous experiments in various environmental conditions. Due to the compact structure and efficiency of the proposed model, it could be implemented in a small embedded system.

Original languageEnglish
Article number5497150
Pages (from-to)2838-2848
Number of pages11
JournalIEEE Transactions on Image Processing
Volume19
Issue number11
DOIs
Publication statusPublished - 2010 Nov

Bibliographical note

Funding Information:
Manuscript received September 24, 2009; revised January 18, 2010; accepted April 20, 2010. Date of publication June 28, 2010; date of current version October 15, 2010. This work was supported by Samsung Electronics Company, Ltd., Suwon, South Korea, and by the World Class University (WCU) program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology under R31-2008-000-10049-0. The work of H. Woo was supported by the Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (2009-0093827). The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Scott T. Acton.

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

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