DocumentCode :
3669561
Title :
Energy based descriptors and their application for car detection
Author :
Radovan Fusek;Eduard Sojka;Karel Mozdřeň;Milan Šurkala
Author_Institution :
Technical University of Ostrava, FEECS, Department of Computer Science, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic
Volume :
1
fYear :
2014
Firstpage :
492
Lastpage :
499
Abstract :
In this paper, we propose a novel technique for object description. The proposed method is based on investigation of energy distribution (in the image) that describes the properties of objects. The energy distribution is encoded into a vector of features and the vector is then used as an input for the SVM classifier. Generally, the technique can be used for detecting arbitrary objects. In this paper, however, we demonstrate the robustness of the proposed descriptors for solving the problem of car detection. Compared with the state-of-the-art descriptors (e.g. HOG, Haar-like features), the proposed approach achieved better results, especially from the viewpoint of dimensionality of the feature vector; the proposed approach is able to successfully describe the objects of interest with a relatively small set of numbers without the use of methods for the reduction of feature vector.
Keywords :
"Detectors","Feature extraction","Automobiles","Temperature distribution","Support vector machines","Training","Image edge detection"
Publisher :
ieee
Conference_Titel :
Computer Vision Theory and Applications (VISAPP), 2014 International Conference on
Type :
conf
Filename :
7294849
Link To Document :
بازگشت