Publication: Detection of People Boarding/Alighting a Metropolitan Train using Computer Vision
Loading...
Identifiers
Publication date
2018-05
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Institution Of Engineering And Technology (IET)
Impact
Export
Abstract
Pedestrian detection and tracking have seen a major progress in the last two decades. Nevertheless there are always appli-cation areas which either require further improvement or that have not been sufficiently explored or where production level performance (accuracy and computing efficiency) has not been demonstrated. One such area is that of pedestrian monitoring and counting in metropolitan railways platforms. In this paper we first present a new partly annotated dataset of a full-size laboratory observation of people boarding and alighting from a public transport vehicle. We then present baseline results for automatic detection of such passengers, based on computer vi-sion, that could open the way to compute variables of interest to traffic engineers and vehicle designers such as counts and flows and how they are related to vehicle and platform layout.
Description
This paper has been presented at : 9th International Conference on Pattern Recognition Systems (ICPRS 2018)
Keywords
Pedestrian detection, HOG, Support vector machine, Deep learning
Bibliographic citation
Belloc, M., Velastin, S.A., Fernández, R. y Jara, M. (2018). Detection of People Boarding/Alighting a Metropolitan Train using Computer Vision. In 9th International Conference on Pattern Recognition Systems (ICPRS 2018).