Research Article Open Access

Embedded Architecture for Object Tracking using Kalman Filter

Ahmad Abdul Qadir Al Rababah1
  • 1 King Abdulaziz University, Saudi Arabia
Journal of Computer Science
Volume 12 No. 5, 2016, 241-245

DOI: https://doi.org/10.3844/jcssp.2016.241.245

Submitted On: 8 September 2015 Published On: 18 May 2016

How to Cite: Al Rababah, A. A. Q. (2016). Embedded Architecture for Object Tracking using Kalman Filter. Journal of Computer Science, 12(5), 241-245. https://doi.org/10.3844/jcssp.2016.241.245

Abstract

Intelligent video is a new area of research fairly wide allowing to do a study, analysis, or interpretation of digital video such as motion analysis. However, for a video surveillance system, a motion analysis task of digital video includes the detection of moving objects and their tracking. The object detection allows the location of the regions of interest, which represents a change of movement. The purpose of tracking is to maintain the identity of objects detected over time by the estimation or the location of their position in each frame of the sequence. The most popular tracking algorithm is the Kalman filtering. In this study a hardware architecture for moving object tracking using Kalman filter on a FPGA board, is proposed.

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Keywords

  • Moving Object Tracking
  • Kalman Filter
  • Hardware Architecture
  • FPGA