Measuring pedestrian trajectories with low cost infrared detectors: Preliminary results.

Armitage, Alistair; Binnie, David; Kerridge, Jon; Lei, Lucy

Abstract

The accurate measurement of pedestrian trajectories has been difficult to achieve in environments other than carefully controlled laboratories. Traditional techniques include direct observation, and analysis of recorded video footage. The Transport Research Institute at Napier University has been using recorded video footage to analyse pedestrian movements for some time. Recently we have started using infrared detectors to record trajectories. Although infrared imaging systems are normally very expensive, a recent commercial product has provided the possibility of low-cost imaging, albeit at low resolutions. The detectors are normally used to count people moving across a line, but we have been reading extra data from the detectors in order to extract complete pedestrian trajectories. Our preliminary studies show that the detectors are very efficient at gathering large amounts of trajectory data. We are also looking at using multiple detectors to cover larger areas. Preliminary results are encouraging, but there are some problems with matching targets as they move between the fields of view of adjacent detectors.

Citation

Armitage, A., Binnie, D., Kerridge, J., & Lei, L. (2003, August). Measuring pedestrian trajectories with low cost infrared detectors: Preliminary results. Presented at 2ND INTERNATIONAL CONFERENCE ON PEDESTRIAN AND EVACUATION DYNAMICS

• Conference Name: 2ND INTERNATIONAL CONFERENCE ON PEDESTRIAN AND EVACUATION DYNAMICS
• Start Date: Aug 20, 2003
• End Date: Aug 22, 2003
• Publication Date: 2003
• Deposit Date: Jun 23, 2008
• Publicly Available Date: Nov 14, 2016
• Peer Reviewed: Peer Reviewed
• Pages: 101-110
• Book Title: Pedestrian and Evacuation Dynamics: 2nd International Conference held at the Old Naval College, University of Greenwich, London, 20-22 August 2003
• ISBN: 9781904521082
• Keywords: Infrared radiation; Motion detectors; Pedestrian behaviour; Computer programming; Computer modelling; Empirical data
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/1809
• Contract Date: Nov 14, 2016