Visible to the public Profiling stationary crowd groups

TitleProfiling stationary crowd groups
Publication TypeConference Paper
Year of Publication2014
AuthorsShuai Yi, Xiaogang Wang
Conference NameMultimedia and Expo (ICME), 2014 IEEE International Conference on
Date PublishedJuly
KeywordsColor, crowd descriptors, crowd video surveillance, Estimation, feature extraction, Filtering, filtering theory, foreground pixel, image motion analysis, Indexes, motion filtering, Noise, object detection, quantitative analysis, spatial-temporal filtering, stationary crowd analysis, Stationary crowd detection, stationary crowd detection algorithm, stationary crowd group detection, stationary crowd groups profiling, Tracking, Trajectory, video signal processing, video surveillance, visual feature extraction

Detecting stationary crowd groups and analyzing their behaviors have important applications in crowd video surveillance, but have rarely been studied. The contributions of this paper are in two aspects. First, a stationary crowd detection algorithm is proposed to estimate the stationary time of foreground pixels. It employs spatial-temporal filtering and motion filtering in order to be robust to noise caused by occlusions and crowd clutters. Second, in order to characterize the emergence and dispersal processes of stationary crowds and their behaviors during the stationary periods, three attributes are proposed for quantitative analysis. These attributes are recognized with a set of proposed crowd descriptors which extract visual features from the results of stationary crowd detection. The effectiveness of the proposed algorithms is shown through experiments on a benchmark dataset.

Citation Key6890138