WPSS: watching people security services

Bouma, Henri; Baan, Jan; Borsboom, Sander; Zon, Kasper van; Luo, Xinghan; Loke, Ben; Stoeller, Bram; Kuilenburg, Hans van; Dijk, J. C. van

doi:10.1117/12.2031639

Cited by 6 publications

(2 citation statements)

References 26 publications

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“…Experiments with human operators showed that the system leads to a significant reduction of missed people by using the interactive functionality, especially for large time intervals [5]. The tracking system was integrated and validated in a crowded [13] [19] shopping mall in the Netherlands, in collaboration with five SMEs [4]. The system performed consistently and robustly.…”

Section: Graphical User Interfacementioning

confidence: 99%

Finding suspects in multiple cameras for improved railway protection

et al. 2014

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The capability to find individuals using CCTV cameras is important for surveillance applications at large areas such as railway stations, airports and shopping centers. However, it is laborious to track and trace people over multiple cameras post incident. In this paper, we describe the live demonstration of our interactive re-identification system in a railway station. The system performs real-time track generation in multiple cameras and live re-identification and refinding of suspects which was live demonstrated in Poland. The system allows fast interactive retrieval of an individual by showing only similar candidates. An operator can find the origin or destination of a person more efficiently, especially over large time and space intervals.

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Section: Graphical User Interfacementioning

confidence: 99%

Finding suspects in multiple cameras for improved railway protection

et al. 2014

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“…These tracks can be used for multi-camera tracking and re-identification [1][19] [6][27] and further behavior analysis [4]. For each person, typically multiple tracks are generated due to presence in different cameras and track fragmentation.…”

Section: Pedestrian Trackingmentioning

confidence: 99%

Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall

et al. 2014

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Rest, "Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall," Proc. SPIE, Vol. 9253, (2014). http://dx.doi. org/10.1117/12.2066851 Copyright 2014 Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only.Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. Automatic detection of suspicious behavior of pickpockets with trackbased features in a shopping mall ABSTRACTProactive detection of incidents is required to decrease the cost of security incidents. This paper focusses on the automatic early detection of suspicious behavior of pickpockets with track-based features in a crowded shopping mall. Our method consists of several steps: pedestrian tracking, feature computation and pickpocket recognition. This is challenging because the environment is crowded, people move freely through areas which cannot be covered by a single camera, because the actual snatch is a subtle action, and because collaboration is complex social behavior. We carried out an experiment with more than 20 validated pickpocket incidents. We used a top-down approach to translate expert knowledge in features and rules, and a bottom-up approach to learn discriminating patterns with a classifier. The classifier was used to separate the pickpockets from normal passers-by who are shopping in the mall. We performed a cross validation to train and evaluate our system. In this paper, we describe our method, identify the most valuable features, and analyze the results that were obtained in the experiment. We estimate the quality of these features and the performance of automatic detection of (collaborating) pickpockets. The results show that many of the pickpockets can be detected at a low false alarm rate.

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Face and Emotion Recognition on Commercial Property under EU Data Protection Law

Lewinski

Trzaskowski

Luzak

2016

Psychology and Marketing

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This paper integrates and cuts through domains of privacy law and biometrics. Specifically, this paper presents a legal analysis on the use of Automated Facial Recognition Systems (the AFRS) in commercial (retail store) settings within the European Union data protection framework. The AFRS is a typical instance of biometric technologies, where a distributed system of dozens of low-cost cameras uses psychological states, sociodemographic characteristics, and identity recognition algorithms on thousands of passers-by and customers. Current use cases and theoretical possibilities are discussed due to the technology's potential of becoming a substantial privacy issue. First, this paper introduces the AFRS and EU data protection law. This is followed by an analysis of European Data protection law and its application in relation to the use of the AFRS, including requirements concerning data quality and legitimate processing of personal data, which, finally, leads to an overview of measures that traders can take to comply with data protection law, including by means of information, consent, and anonymization.

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WPSS: watching people security services

Cited by 6 publications

References 26 publications

Finding suspects in multiple cameras for improved railway protection

Finding suspects in multiple cameras for improved railway protection

Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall

Face and Emotion Recognition on Commercial Property under EU Data Protection Law

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