Visual recognition of crowd dynamics has had a huge impact on several applications
including surveillance, situation awareness, homeland security and intelligent environments …

Lagrangian theory provides a rich set of tools for analyzing non-local, long-term motion
information in computer vision applications. Based on this theory, we present a specialized …

The performance of optical flow algorithms greatly depends on the specifics of the content
and the application for which it is used. Existing and well established optical flow datasets …

Bottleneck situations can occur in overcrowded areas such as entrances or narrowed
passages and are associated with a great danger to the life and health of involved people …

Flow segmentation based on similar motion patterns in crowded scenes remains an open
problem in computer vision due to inherent complexity and vast diversity found in such …

Lagrangian theory provides a diverse set of tools for continuous motion analysis. Existing
work shows the applicability of Lagrangian methods for video analysis in several aspects. In …

Modeling of crowd and pedestrian dynamics has intrigued engineers, physicists, and
sociologists alike, even in recent times. Scientists have long sought to model the collective …

Automatically detecting anomaly in surveillance videos is a crucial issue for social security.
Motion instability based online abnormal behaviors detection has been developed in an …

The availability of dense motion information in computer vision domain allows for the
effective application of Lagrangian techniques that have their origin in fluid flow analysis and …

针对暴力行为识别过程中缺乏描述不同时间尺度下暴力行为运动变化的问题,
本文提出了一种基于拉格朗日场的多级运动特征暴力行为识别算法. 该算法将描述非线性粒子 …