Sciweavers

Share
DAGM
2004
Springer

Efficient Face Detection by a Cascaded Support Vector Machine Using Haar-Like Features

9 years 11 months ago
Efficient Face Detection by a Cascaded Support Vector Machine Using Haar-Like Features
Abstract. In this paper, we present a novel method for reducing the computational complexity of a Support Vector Machine (SVM) classifier without significant loss of accuracy. We apply this algorithm to the problem of face detection in images. To achieve high run-time efficiency, the complexity of the classifier is made dependent on the input image patch by use of a Cascaded Reduced Set Vector expansion of the SVM. The novelty of the algorithm is that the Reduced Set Vectors have a Haar-like structure enabling a very fast SVM kernel evaluation by use of the Integral Image. It is shown in the experiments that this novel algorithm provides, for a comparable accuracy, a 200 fold speed-up over the SVM and an 6 fold speed-up over the Cascaded Reduced Set Vector Machine.
Matthias Rätsch, Sami Romdhani, Thomas Vetter
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where DAGM
Authors Matthias Rätsch, Sami Romdhani, Thomas Vetter
Comments (0)
books