Citation

Jiménez AC, Anzola J, Jimenez-Triana A. Heliyon 2019; 5(4): e01449.

Affiliation

Department of Control Engineering, Universidad Distrital Francisco José de Caldas, Cll 74 Sur No. 68A - 20, Bogotá, Colombia.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.heliyon.2019.e01449

PMID

31008391

PMCID

PMC6458473

Abstract

Counting the number of pedestrians in urban environments has become an area of interest over the past few years. Its applications include studies to control vehicular traffic lights, urban planning, market studies, and detection of abnormal behaviors. However, these tasks require the use of intelligent algorithms of high computational demand that need to be trained in the environment being studied. This article presents a novel method to estimate pedestrian flow in uncontrolled environments by using the fractal dimension measured through the box-counting algorithm, which does not require the use of image pre-processing and intelligent algorithms. Four scenarios were used to validate the method presented in this article, of which the last scene was a low-light surveillance video, showing experimental results with a mean relative error of 4.92% when counting pedestrians. After comparing the results with other techniques that depend on intelligent algorithms, we can confirm that this method achieves improved performance in the estimation of pedestrian traffic.

Language: en

Keywords

Computer science