Visual Analysis of Human Movement Data

In this paper we present our visual analysis results of visitor movement data in an amusement park during a weekend. We assume most people move among several amusement park spots in a specific pattern. And for few people whose movement pattern don’t belong to any group we assume, we pay special concern about their route for they may related to a crime happened in amusement park during the weekend. All of this is done in a way that we visualization visitors’ movement data into specific route and apply visual analysis to it. By extracting check-in data we identify spots in amusement park visitor tend to come and stay, other movement data show how visitor move from one spot to another. Combine the trip among spots and stay in spots we extract every route of individual visitor. Once this is done for all, we use visual analysis to group visitors into different clusters. Each cluster has a special movement pattern, people belonging to same cluster tend to have similar movement pattern or move in a small group (however people in one small group are not necessarily in a same cluster). We .apply this cluster group to all visitors and for those anomalies that do not belong to any of them we check their individual route to see their potential relation to the crime. Additionally but also uncertainly we will try to use exist cluster movement pattern to predict ungroup data .