Home // ICONS 2014, The Ninth International Conference on Systems // View article
Authors:
Ramiro Pereira de Magalhães
Cabral Lima
Keywords: pattern detection; Viola-Jones framework; Adaboost; Haar wavelet; principal component analysis
Abstract:
This paper proposes a new weight assignment method for Haar-like features. The method uses principal component analysis (PCA) over the positive training instances to assign new weights to the features. Together with the method, a particular Haar-like feature that uses statistics extracted from positive training instances is employed. The method and the Haar-like feature were designed to verify if the distribution of points produced from the negative instances in the single rectangle feature space (SRFS) of each Haar-like feature could be modeled as an uniform distribution. Although negative instances may spread themselves in very different and chaotic ways through the SRFS, experiment with the method and the Haar-like feature has shown that the negative instance cannot be properly modeled as an uniform distribution.
Pages: 55 to 62
Copyright: Copyright (c) IARIA, 2014
Publication date: February 23, 2014
Published in: conference
ISSN: 2308-4243
ISBN: 978-1-61208-319-3
Location: Nice, France
Dates: from February 23, 2014 to February 27, 2014