Interpreting pedestrian behaviour by visualising and clustering movement data

Gavin McArdle*, Urška Demšar, Stefan Van Der Spek, Seán McLoone

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges. Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This paper introduces such a geovisual analytics environment for exploring movement trajectories, which provides visualisation interfaces, based on the classic space-time cube. Additionally, a new approach, using the mathematical description of motion within a space-time cube, is used to determine the similarity of trajectories and forms the basis for clustering them. These techniques were used to analyse pedestrian movement. The results reveal interesting and useful spatiotemporal patterns and clusters of pedestrians exhibiting similar behaviour.
Original languageEnglish
Title of host publicationWeb and Wireless Geographical Information Systems
Pages64-81
Number of pages18
Volume7820
DOIs
Publication statusPublished - 11 Apr 2013
Event12th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2013 - AB, Banff, Canada
Duration: 04 Apr 201305 Apr 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7820 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference12th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2013
CountryCanada
CityBanff
Period04/04/201305/04/2013

Keywords

  • Clustering
  • Geovisual Analysis
  • Movement Data Analysis
  • Space-time Cube

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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