Object classification using CNN for video traffic detection system

Abstract

Recently, a lot of research on the use of big data is made, and this paper was aimed to perform classification experiments using CNN for the detected object collected from traffic detectors. In addition the experimental results were compared with the HOG descriptor that is commonly used in existing pedestrian and object classification and wavelet, texture and descriptor that are used in the road surface condition classification. According to the results after applied to the collected RVFTe-10 data, the performances of HOG SVM and CNN were excellent by showing 99.9% and 99.5% respectively.