Authors:
Radovan Fusek
;
Eduard Sojka
;
Karel Mozdřeň
and
Milan Šurkala
Affiliation:
Technical University of Ostrava and FEECS, Czech Republic
Keyword(s):
Object Detection, Recognition, SVM, Image Descriptors, Feature Selection.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Feature Selection and Extraction
;
Object Recognition
;
Pattern Recognition
;
Shape Representation
;
Software Engineering
;
Theory and Methods
Abstract:
In the paper, we propose the novel and efficient object descriptors that are designed to describe the appearance
of the objects. The descriptors are called as Hierarchical Energy-Transfer Features (HETF). The main idea
behind HETF is that the shape of the objects can be described by the function of energy distribution. In the
image, the transfer of energy is solved by making use of physical laws. The function of the energy distribution
is obtained by sampling, after the energy transfer process; the image is divided into the cells of variable sizes
and the values of the function is investigated inside each cell. The proposed descriptors achieved very good
detection results compared with the state-of-the-art methods (e.g. Haar, HOG, LBP features). We show the
robustness of the descriptors for solving the face detection problem.