Section: New Results

Crowd Event Monitoring Using Texture and Motion Analysis

Participants : Vaibhav Katiyar, Jihed Joober, François Brémond.

keywords: Crowd Event, Texture Analysis, GLCM, Optical Flow

The aim of this work is to monitor crowd event using crowd density, change of speed and orientation of group of people. For reducing complexity we are using human density rather than individual human detection and tracking. In this study Human density is quantified mainly into three groups- (1) Empty (2) Sparse (3) Dense. These are approximated by calculating Haralick features from Grey Level Co-occurrence Matrix (GLCM).

We use Optical flow for getting motion information like current speed and orientation of selected FAST feature points. Subsequently we used this information for classifying crowd behaviour into normal or abnormal categories wherein we seek for sudden change in speed or orientation heterogeneity for abnormal behaviour.

In future work this abnormal behaviour may further be classified into different events like Running, Collecting, Dispersion, Stopping/Blocking.