The paper proposes an improved hardware implementation of the OpenCV version of the Gaussian Mixture Model (GMM) algorithm. Truncated binary multipliers and a ROM compression technique are employed to reduce hardware complexity while increasing circuit processing capability. The OpenCV GMM algorithm is adapted to allow the FPGA implementation while providing a minimal impact on the quality of the processed videos. When implemented on Virtex5 FPGA the proposed circuit is able to process High Definition (HD) video sequences at 30 frame per second (fps) improving the performances with respect to previously proposed implementations (-7.6% in area and +12.6% in speed).
An FPGA-based Real-time Background Identification Circuit for 1080p Video / Genovese, Mariangela; Napoli, Ettore. - STAMPA. - (2012), pp. 330-335. (Intervento presentato al convegno Signal Image Technology and Internet Based Systems (SITIS), 2012 Eighth International Conference on tenutosi a Sorrento (I) nel 25-29 Nov. 2012) [10.1109/SITIS.2012.55].
An FPGA-based Real-time Background Identification Circuit for 1080p Video
GENOVESE, MARIANGELA;NAPOLI, ETTORE
2012
Abstract
The paper proposes an improved hardware implementation of the OpenCV version of the Gaussian Mixture Model (GMM) algorithm. Truncated binary multipliers and a ROM compression technique are employed to reduce hardware complexity while increasing circuit processing capability. The OpenCV GMM algorithm is adapted to allow the FPGA implementation while providing a minimal impact on the quality of the processed videos. When implemented on Virtex5 FPGA the proposed circuit is able to process High Definition (HD) video sequences at 30 frame per second (fps) improving the performances with respect to previously proposed implementations (-7.6% in area and +12.6% in speed).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
