A comparative study of outlier detection for large-scale traffic data by one-class SVM and kernel density estimation

Henry Y. T. Ngan; Nelson H. C. Yung; Anthony G. O. Yeh

doi:10.1117/12.2078250

27 February 2015 A comparative study of outlier detection for large-scale traffic data by one-class SVM and kernel density estimation

Henry Y. T. Ngan, Nelson H. C. Yung, Anthony G. O. Yeh

Author Affiliations +

Proceedings Volume 9405, Image Processing: Machine Vision Applications VIII; 94050I (2015) https://doi.org/10.1117/12.2078250
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

This paper aims at presenting a comparative study of outlier detection (OD) for large-scale traffic data. The traffic data nowadays are massive in scale and collected in every second throughout any modern city. In this research, the traffic flow dynamic is collected from one of the busiest 4-armed junction in Hong Kong in a 31-day sampling period (with 764,027 vehicles in total). The traffic flow dynamic is expressed in a high dimension spatial-temporal (ST) signal format (i.e. 80 cycles) which has a high degree of similarities among the same signal and across different signals in one direction. A total of 19 traffic directions are identified in this junction and lots of ST signals are collected in the 31-day period (i.e. 874 signals). In order to reduce its dimension, the ST signals are firstly undergone a principal component analysis (PCA) to represent as (x,y)-coordinates. Then, these PCA (x,y)-coordinates are assumed to be conformed as Gaussian distributed. With this assumption, the data points are further to be evaluated by (a) a correlation study with three variant coefficients, (b) one-class support vector machine (SVM) and (c) kernel density estimation (KDE). The correlation study could not give any explicit OD result while the one-class SVM and KDE provide average 59.61% and 95.20% DSRs, respectively.

Citation Download Citation

Henry Y. T. Ngan, Nelson H. C. Yung, and Anthony G. O. Yeh "A comparative study of outlier detection for large-scale traffic data by one-class SVM and kernel density estimation", Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050I (27 February 2015); https://doi.org/10.1117/12.2078250

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