Abstract
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 $2.72$cm when estimating the future motion of 32 pedestrians with more than 2 seconds in advance. This paper discusses this and other results.
Abstract (translated)
虽然人类和群体分析在过去几十年中已成为一个重要领域，但一些当前和相关的应用涉及到在真实视频序列中估计行人未来的运动。本文提出了一种基于人流仿真的实时行人运动估计方法。我们的方法是基于物理和启发式方法，利用生物网格作为群体模拟方法来估计视频序列中人的未来位置。结果表明，即使对于可能发生事件的复杂视频，我们的估计方法也能很好地工作。当提前2秒以上估计32个行人的未来运动时，最大实现的平均误差为2.72美元厘米。本文讨论了这一点和其他结果。
URL
https://arxiv.org/abs/1904.05448
