Local and global information exchange for enhancing object detection and tracking

Jinseok Lee, Shung Han Cho, Seong Jun Oh, Sangjin Hong

Research output: Contribution to journalArticlepeer-review


Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

Original languageEnglish
Pages (from-to)1400-1420
Number of pages21
JournalKSII Transactions on Internet and Information Systems
Issue number5
Publication statusPublished - 2012 May 25


  • Data combination
  • Distributed detection system
  • Information exchange
  • Localization
  • Sensor network
  • Visual sensor

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications


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