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- W1556327589 abstract "In this paper we propose a human detection framework based on an enhanced version of Histogram of Oriented Gradients (HOG) features. These feature descriptors are computed with the help of a precalculated histogram of square-blocks. This novel method outperforms the integral of oriented histograms allowing the calculation of a single feature four times faster. Using Adaboost for HOG feature selection and Support Vector Machine as weak classifier, we build up a real-time human classifier with an excellent detection rate." @default.
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- W1556327589 date "2007-01-01" @default.
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- W1556327589 title "Enhancing Real-Time Human Detection Based on Histograms of Oriented Gradients" @default.
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- W1556327589 doi "https://doi.org/10.1007/978-3-540-75175-5_91" @default.
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