Browsing by Author "Karaimer, Hakkı Can"
Now showing items 1-6 of 6
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Combining shape-based and gradient-based classifiers for vehicle classification
Karaimer, Hakkı Can; Çınaroğlu, İbrahim; Baştanlar, Yalın (IEEE, 2015-10)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 ... -
Correction to: Detection and classification of vehicles from omnidirectional videos using multiple silhouettes
Karaimer, Hakkı Can; Barış, İpek; Baştanlar, Yalın (Springer, 2018-08)An acknowledgements section was missing in this paper. It should read as follows: -
Detection and classification of vehicles from omnidirectional videos using multiple silhouettes
Karaimer, Hakkı Can; Barış, İpek; Baştanlar, Yalın (Springer, 2017-08)To detect and classify vehicles in omnidirectional videos, we propose an approach based on the shape (silhouette) of the moving object obtained by background subtraction. Different from other shape-based classification ... -
Detection and classification of vehicles from omnidirectional videos using temporal average of silhouettes
Karaimer, Hakkı Can; Baştanlar, Yalın (INSTICC, 2015)This paper describes an approach to detect and classify vehicles in omnidirectional videos. The proposed classification method is based on the shape (silhouette) of the detected moving object obtained by background ... -
Shape based detection and classification of vehicles using omnidirectional videos
Karaimer, Hakkı Can (Izmir Institute of Technology, 2015-06)To detect and classify vehicles in omnidirectional videos, an approach based on the shape (silhouette) of the moving object obtained by background subtraction is proposed. Different from other shape based classification ... -
The visual object tracking VOT2013 challenge results
Kristan, Matej; Pflugfelder, Roman; Leonardis, Ales; Matas, Jiri; Porikli, Fatih; Cehovin, Luka; Nebehay, Georg; Fernandez, Gustavo; Vojir, Tomas; Gatt, Adam; Khajenezhad, Ahmad; Salahledin, Ahmed; Soltani-Farani, Ali; Zarezade, Ali; Petrosino, Alfredo; Milton, Anthony; Bozorgtabar, Behzad; Li, Bo; Chan, Chee Seng; Heng, Cher Keng; Ward, Dale; Kearney, David; Monekosso, Dorothy; Karaimer, Hakkı Can; Rabiee, Hamid R.; Zhu, Jianke; Gao, Jin; Xiao, Jingjing; Zhang, Junge; Xing, Junliang; Huang, Kaiqi; Lebeda, Karel; Cao, Lijun; Maresca, Mario Edoardo; Lim, Mei Kuan; El Helw, Mohamed; Felsberg, Michael; Remagnino, Paolo; Bowden, Richard; Goecke, Roland; Stolkin, Rustam; Lim, Samantha YueYing; Maher, Sara; Poullot, Sebastien; Wong, Sebastien; Satoh, Shin’ichi; Chen, Weihua; Hu, Weiming; Zhang, Xiaoqin; Li, Yang; Zhi Heng, Niu (IEEE, 2013)Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the ...
