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 fast human classifier with an excellent detection rate.
CitationPerdersoli, Marco; Gonzàlez, Jordi; Chakraborty, Bhaskar; Villanueva, Juan J.. "Boosting histograms of oriented gradients for human detection". A: 2nd Computer Vision: Advances in Research & Development (CVCRD), Bellaterra, Espanya, 2007. s. n., 2007, p. 1-6.
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