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|Title:||Classification of vehicles using binary foreground images averaged over time||Authors:||Karaimer, Hakkı Can
|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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