Visible to the public VisLoiter+: An Entropy Model-Based Loiterer Retrieval System with User-Friendly Interfaces

TitleVisLoiter+: An Entropy Model-Based Loiterer Retrieval System with User-Friendly Interfaces
Publication TypeConference Paper
Year of Publication2018
AuthorsSandifort, Maguell L.T.L., Liu, Jianquan, Nishimura, Shoji, Hürst, Wolfgang
Conference NameProceedings of the 2018 ACM on International Conference on Multimedia Retrieval
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-5046-4
Keywordsentropy model, heatmap, Human Behavior, loiterer retrieval, loitering discovery, Metrics, pubcrawl, ranking system, Resiliency, video surveillance
Abstract

It is very difficult to fully automate the detection of loitering behavior in video surveillance, therefore humans are often required for monitoring. Alternatively, we could provide a list of potential loiterer candidates for a final yes/no judgment of a human operator. Our system, VisLoiter+, realizes this idea with a unique, user-friendly interface and by employing an entropy model for improved loitering analysis. Rather than using only frequency of appearance, we expand the loiter analysis with new methods measuring the amount of person movements across multiple camera views. The interface gives an overview of loiterer candidates to show their behavior at a glance, complemented by a lightweight video playback for further details about why a candidate was selected. We demonstrate that our system outperforms state-of-the-art solutions using real-life data sets.

URLhttps://dl.acm.org/citation.cfm?doid=3206025.3206091
DOI10.1145/3206025.3206091
Citation KeysandifortVisLoiterEntropyModelBased2018