The paper proposes the hardware implementation of the Gaussian Mixture Model (GMM) algorithm included in the OpenCV library. The OpenCV GMM algorithm is adapted to allow the FPGA implementation while providing a minimal impact on the quality of the processed videos. The circuit performs 30 frame per second (fps) background (Bg) identification on High Definition (HD) video sequences when implemented on commercial FPGA and outperforms previously proposed implementations. When implemented on Virtex5 lx50 FPGA using one level of pipeline, runs at 95.3 MHz, uses 5.3% of FPGA resources with a power dissipation of 1.47 mW/MHz.

FPGA implementation of OpenCV compatible background identification circuit

E. Napoli
2012-01-01

Abstract

The paper proposes the hardware implementation of the Gaussian Mixture Model (GMM) algorithm included in the OpenCV library. The OpenCV GMM algorithm is adapted to allow the FPGA implementation while providing a minimal impact on the quality of the processed videos. The circuit performs 30 frame per second (fps) background (Bg) identification on High Definition (HD) video sequences when implemented on commercial FPGA and outperforms previously proposed implementations. When implemented on Virtex5 lx50 FPGA using one level of pipeline, runs at 95.3 MHz, uses 5.3% of FPGA resources with a power dissipation of 1.47 mW/MHz.
2012
9780415621342
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4772745
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