The sampling, the preprocessing, and the modeling for the commercial street pedestrian traffic flow data based on the intelligent video analysis are presented in this paper. The Xidan mall is taken as an example, the by-date grouping-style vertical time series are established, consisting of multi surveillance points and different points-in-time. The modeling and forecast results show that all vertical time series are stationary and of non-white noise with similar ARMA expression formulas, which can be well applied to the forecast of pedestrian traffic flow data.

intelligent video analysis  /  commercial street pedestrian traffic flow  /  forecast model