FPGA Implementation of the Flux Tensor Moving Object Detection Method

  • Piotr Janus
  • Kamil Piszczek
  • Tomasz Kryjak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9972)


In this paper a hardware implementation in a field programmable gate array (FPGA) device of moving object segmentation using the flux tensor (FT) method is presented. The used algorithm and its parallelized version are described in details. The designed module has been verified on the VC 707 development board with Virtex 7 FPGA device for the following video stream parameters: \(720 \times 576\) @ 50 fps (25 MHz pixel clock), \(1280 \times 720\) @ 50 fps (74.25 MHz pixel clock) and \(1920 \times 1080\) @ 50 fps (148.5 MHz pixel clock). Additionally, the computing performance and power consumption have been estimated. The proposed module outperforms the previous FT implementations both in terms of real-time processing capabilities for high-definition stream, as well as energy efficiency.


Field Programmable Gate Array Video Stream Move Object Detection Optical Flow Computation Field Programmable Gate Array Implementation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work presented in this paper was supported by AGH University of Science and Technology project number


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical EngineeringAGH University of Science and TechnologyKrakówPoland

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