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Title: Combining shape-based and gradient-based classifiers for vehicle classification
Authors: Karaimer, Hakkı Can
Çınaroğlu, İbrahim
Baştanlar, Yalın
Keywords: Combined classifier
Histogram of oriented gradients
Omnidirectional cameras
Vehicle classification
Gradient based
Shape based
Issue Date: Oct-2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Karaimer, H. C., Çınaroğlu, İ., and Baştanlar, Y. (2015, September). Combining shape-based and gradient-based classifiers for vehicle classification. Paper presented at the 18th IEEE International Conference on Intelligent Transportation Systems. doi:10.1109/ITSC.2015.135
Abstract: In this paper, we present our work on vehicle classification with omnidirectional cameras. In particular, we investigate whether the combined use of shape-based and gradient-based classifiers outperforms the individual classifiers or not. For shape-based classification, we extract features from the silhouettes in the omnidirectional video frames, which are obtained after background subtraction. Classification is performed with kNN (k Nearest Neighbors) method, which has been commonly used in shape-based vehicle classification studies in the past. For gradient-based classification, we employ HOG (Histogram of Oriented Gradients) features. Instead of searching a whole video frame, we extract the features in the region located by the foreground silhouette. We use SVM (Support Vector Machines) as the classifier since HOG+SVM is a commonly used pair in visual object detection. The vehicle types that we worked on are motorcycle, car and van (minibus). In experiments, we first analyze the performances of shape-based and HOG-based classifiers separately. Then, we analyze the performance of the combined classifier where the two classifiers are fused at decision level. Results show that the combined classifier is superior to the individual classifiers. © 2015 IEEE.
Description: 18th IEEE International Conference on Intelligent Transportation Systems, ITSC 2015; Palacio de Congresos de Canarias Avenida Principe de Asturias Gran Canaria; Spain; 15 September 2015 through 18 September 2015
ISSN: 2153-0009
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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