Towards using particle filtering for increasing error correction accuracy in traffic surveillance applications

This paper analyzes and compares two error correction algorithms in context of traffic control applications. They are the Sequential Importance Sampling (SIS) and the Sequential Importance Resampling (SIR). Performances of both algorithms are analyzed and conclusions are drawn. Moreover, experimental results prove that algorithms´ parameters have a great impact on their performances.