Boosting Histograms of Oriented Gradients for Human Detection
نویسندگان
چکیده
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 squareblocks. 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.
منابع مشابه
’Histograms of Oriented Gradients for Human Detection’ versus ’Fast Human Detection Using a Cascade of Histograms of Oriented Gradients’
Dalal and Triggs [1] studied the question of feature sets for robust visual object recognition. They first considered existing edge and gradient based descriptors and then they showed experimentally that grids of Histograms of Oriented Gradients (HoG) descriptors significantly outperform existing feature sets for human detection. After this they studied the influence of each stage of the comput...
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