DocumentCode
263492
Title
Vehicle Type Classification from Surveillance Videos on Urban Roads
Author
Yu-Chen Wang ; Cheng-Ta Hsieh ; Chin-Chuan Han ; Kuo-Chin Fan
Author_Institution
Inst. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Jhongli, Taiwan
fYear
2014
fDate
12-14 July 2014
Firstpage
266
Lastpage
270
Abstract
In this paper, a novel classification scheme has been proposed for real time vehicle type classification from surveillance videos on urban roads. Three kinds of vehicle types, i.e., Small cars, large cars, and motorbikes, are classified for the later retrieval. This system is performed in various outdoor illumination and weather conditions. The average precision and recall rates of vehicle type classification are more than 93.82% and 88%, respectively. Moreover, the performance of the proposed method is up to 25 frames per seconds.
Keywords
automobiles; image classification; motorcycles; traffic engineering computing; video retrieval; video signal processing; video surveillance; large cars; motorbikes; outdoor illumination; small cars; urban roads; vehicle type classification scheme; video surveillance; weather conditions; Feature extraction; Histograms; Image color analysis; Motorcycles; Surveillance; Videos; Histogram of Gradient (HOG) features; Vehicle type classification; video retrieval; video surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Ubi-Media Computing and Workshops (UMEDIA), 2014 7th International Conference on
Conference_Location
Ulaanbaatar
Print_ISBN
978-1-4799-4267-1
Type
conf
DOI
10.1109/U-MEDIA.2014.69
Filename
6916366
Link To Document