Paper Info
Title
People Tracking Using Laser Range Scanners And Vision
Abstract
Tracking multiple crossing people is a great challenge, since common algorithms tend to loose some or the persons or to interchange their identities when they get close to each other and split up again. In several consecutive papers it was possible to develop an algorithm using data from laser range scanners which is able to track an arbitrary number of crossing people without any loss of track. In this paper we address the problem of rediscovering the identities of the persons after a crossing. Therefore, a camera system is applied. An infrared camera detects the people in the observation area and then a charge-coupled device camera is used to extract the colour information about those people. For the representation of the colour information the HSV colour space is applied using a histogram. Before the crossing the system learns the mean and the standard deviation of the colour distribution of each person. After the crossing the system relocates the identities by comparing the actually measured colour distributions with the distributions learnt before the crossing. Thereby, a Gaussian distribution of the colour values is assumed. The most probably assignment of the identities is then found using Munkres' Hungarian algorithm. It is proven with data from real world experiments that Our approach can reassign the identities of the tracked persons stable after a crossing.
Year
Venue
Keywords
2008
ICINCO 2008: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL RA-1: ROBOTICS AND AUTOMATION, VOL 1
people tracking, crossing targets, laser range scanners, vision, HSV colour space
Field
DocType
Citations 
Computer vision,Laser,Artificial intelligence,Engineering
Conference
1
PageRank 
References 
Authors
0.36
1
4
Name
Order
Citations
PageRank
Andreas Kräußling1122.54
Bernd Brüggemann2246.83
Dirk Schulz31701236.54
Armin B. Cremers42287446.79