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
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;
Conference_Titel :
Ubi-Media Computing and Workshops (UMEDIA), 2014 7th International Conference on
Conference_Location :
Ulaanbaatar
Print_ISBN :
978-1-4799-4267-1
DOI :
10.1109/U-MEDIA.2014.69