Publication
Enhancing real-time human detection based on histograms of oriented gradients
Conference Article
Conference
International Conference on Computer Recognition Systems (CORES)
Edition
5th
Pages
739-746
Doc link
http://dx.doi.org/10.1007/978-3-540-75175-5_91
File
Authors
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Pedersoli, Marco
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Gonzàlez Sabaté, Jordi
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Chakraborty, Bhaskar
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Villanueva Pipaón, Juan José
Projects associated
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.
Categories
computer vision.
Scientific reference
M. Pedersoli, J. Gonzàlez, B. Chakraborty and J.J. Villanueva. Enhancing real-time human detection based on histograms of oriented gradients, 5th International Conference on Computer Recognition Systems, 2007, Wroclaw, Polònia, in Computer Recognition Systems 2, Vol 45 of Advances in Soft Computing, pp. 739-746, 2007, Springer.
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