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.
Original language | English |
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Title of host publication | ICMR 2018 - Proceedings of the 2018 ACM International Conference on Multimedia Retrieval |
Publisher | Association for Computing Machinery |
Pages | 505-508 |
Number of pages | 4 |
ISBN (Print) | 9781450350464 |
DOIs | |
Publication status | Published - 5 Jun 2018 |
Event | 8th ACM International Conference on Multimedia Retrieval, ICMR 2018 - Yokohama, Japan Duration: 11 Jun 2018 → 14 Jun 2018 |
Conference
Conference | 8th ACM International Conference on Multimedia Retrieval, ICMR 2018 |
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Country/Territory | Japan |
City | Yokohama |
Period | 11/06/18 → 14/06/18 |
Keywords
- Entropy model
- Heatmap
- Loiterer retrieval
- Loitering discovery
- Ranking system
- Video surveillance