Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9925
Title: Classification of vehicles using binary foreground images averaged over time
Authors: Karaimer, Hakkı Can
Baştanlar, Yalın
Keywords: Omnidirectional camera
Omnidirectional video
Vehicle detection
Vehicle classification
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Series/Report no.: Signal Processing and Communications Applications Conference
Abstract: We describe a shape-based method for classification of vehicles from omnidirectional videos. Different from similar approaches, the binary images of vehicles obtained by background subtraction in a sequence of frames are averaged over time. We show with experiments that using the average shape of the object results in a more accurate classification than using a single frame. The vehicle types we classify are motorcycle, car and van. We created an omnidirectional video dataset and repeated experiments with shuffled train-test sets to ensure randomization.
Description: 23nd Signal Processing and Communications Applications Conference (SIU)
URI: https://hdl.handle.net/11147/9925
ISBN: 978-1-4673-7386-9
ISSN: 2165-0608
Appears in Collections:WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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