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A fixed-point implementation and performance analysis of EGML moving object detection algorithm
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 Title & Authors
A fixed-point implementation and performance analysis of EGML moving object detection algorithm
An, Hyo-sik; Kim, Gyeong-hun; Shin, Kyung-wook;
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 Abstract
An analysis of hardware design conditions of moving object detection (MOD) algorithm is described, which is based on effective Gaussian mixture learning (EGML). A simulation model of EGML algorithm is implemented using OpenCV, and the effects of some parameter values on background learning time and MOD sensitivity are analyzed for various images. In addition, optimal design conditions for hardware implementation of EGML-based MOD algorithm are extracted from fixed-point simulations for various bit-widths of parameters. The proposed fixed-point model of the EGML-based MOD uses only half of the bit-width at the expense of the loss of MOD performance within 0.5% when compared with floating-point MOD results.
 Keywords
moving object detection;MOD;Gaussian mixture model;EGML;background learning;
 Language
Korean
 Cited by
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