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

Henri Bouma; Jan Baan; Gertjan J. Burghouts; Pieter T. Eendebak; Jasper R. van Huis; Judith Dijk; Jeroen H. C. van Rest

doi:10.1117/12.2066851

7 October 2014 Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall

Henri Bouma, Jan Baan, Gertjan J. Burghouts, Pieter T. Eendebak, Jasper R. van Huis, Judith Dijk, Jeroen H. C. van Rest

Proceedings Volume 9253, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence X; and Optical Materials and Biomaterials in Security and Defence Systems Technology XI; 92530F (2014) https://doi.org/10.1117/12.2066851
Event: SPIE Security + Defence, 2014, Amsterdam, Netherlands

Abstract

Proactive 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.

Citation Download Citation

Henri Bouma, Jan Baan, Gertjan J. Burghouts, Pieter T. Eendebak, Jasper R. van Huis, Judith Dijk, and Jeroen H. C. van Rest "Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall", Proc. SPIE 9253, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence X; and Optical Materials and Biomaterials in Security and Defence Systems Technology XI, 92530F (7 October 2014); https://doi.org/10.1117/12.2066851

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available