Crowd Analysis at Mass Transit Sites Prahlad Kilambi, Osama Masound, and Nikolaos Papanikolopoulos...
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Transcript of Crowd Analysis at Mass Transit Sites Prahlad Kilambi, Osama Masound, and Nikolaos Papanikolopoulos...
Crowd Analysis at Mass Transit Sites
Prahlad Kilambi, Osama Masound, and Nikolaos
Papanikolopoulos
University of Minnesota
Proceedings of IEEE ITSC 20062006 IEEE Intelligent Transportation Systems Conference
abstract
Detecting and estimating the count of groups, dense, and tracking them. The system can estimate in real-time. No constraints on camera placement Groups are tracked using Kalman filtering
techniques
Introduction
Previous proposed methods can’t count number of people, and track the crowds in real-time If the number of individuals increases, the system
degrades drastically.
e.g. Counts of people is used for crowd control.
Related Work
Crowd monitoring using image processing, A. David Color pixels and edge pixels based
W4: A real time system for detecting and tracking people, I. Haritaoglu Tracking individuals based on shape models
Automatic estimation of crowd density using texture, A. Marana Estimate crowd density using neural network
Bayesian human segmentation in crowded situations, T. Zhao Using Bayesian model
Overview of the Algorithm
There are two mode of tracking people Tracks individuals
Kalman filter technique count the number of people in group
Extended Kalman filter tracker
Based on humans, in general, move together with fixed gap between them
Tracking
Two purposes Avoid a number of false alarms including those due to other
moving objects in the scene Occlusion handling
Kalman filter tracker is valid for both single pedestrian and groups
There are 3 tracking steps for occlusion handling
Individuals or groups(Individual are taller
than wider)
People or vehicle(velocity threshold)
If classified as group,Group tracker is initialized.
Experiments
Experiments’ Settings three difference scene 8 difference positions camera height was varied from 27 feet to 90 feet the tilt of camera was varied from 20 to 40 degrees most crowded scene is up to 40 people
Test PC Pentium 4 3.0 GHz