2019/04/10 by Cliceres dal Bianco, Bianco, Cliceres dal, Soraia Raupp Musse +1
Computer Science · Engineering · #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #Evacuation and Crowd Dynamics #FOS: Computer and information sciences #Graphics (cs.GR) #Video Surveillance and Tracking Methods
paper · pdf · doi:10.48550/arxiv.1904.05448
openalex publication_date 2019/04/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
While human and group analysis have become an important area in last decades, some current and relevant applications involve to estimate future motion of pedestrians in real video sequences. This paper presents a method to provide motion estimation of real pedestrians in next seconds, using crowd simulation. Our method is based on Physics and heuristics and use BioCrowds as crowd simulation methodology to estimate future positions of people in video sequences. Results show that our method for estimation works well even for complex videos where events can happen. The maximum achieved average error is 2.72cm when estimating the future motion of 32 pedestrians with more than 2 seconds in advance. This paper discusses this and other results.