Reference-based person re-identification

An, Le; Kafai, Mehran; Yang, Songfan; Bhanu, Bir

doi:10.1109/avss.2013.6636647

Cited by 65 publications

(61 citation statements)

References 10 publications

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“…Het automatisch volgen van mensen in één camera in rustige omgevingen is een volwassen technologie geworden die wordt gebruikt in diverse toepassingen 2 . De automatische mensdetectie systemen die zijn geïntegreerd in de camera zijn vaak gebaseerd op beweging in het camerabeeld.…”

Section: Detecteren En Volgen Van Mensen In ééN Cameraunclassified

“…of "Waar ging hij naartoe na een incident?". Aan de andere kant is het ook een 'enabling' technologie omdat de opgebouwde tracks informatie bevatten over het looppatroon en omdat deze technologie het mogelijk maakt om zwakke 2 3 . In het Engels wordt deze functionaliteit ook wel 'tracing', 'multi-camera tracking', 'forensic search' of 'person re-identification' (Gong, 2014) (Rest et al, 2009).…”

Section: Volgen Van Mensen Over Meerdere Camera'sunclassified

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Automatische gedragsanalyse voor effectiever cameratoezicht in de openbare ruimte

Bouma¹,

Rest²,

Burghouts³

et al. 2014

Tijdschrift Voor Veiligheid

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Section: Detecteren En Volgen Van Mensen In ééN Cameraunclassified

Section: Volgen Van Mensen Over Meerdere Camera'sunclassified

Automatische gedragsanalyse voor effectiever cameratoezicht in de openbare ruimte

Bouma¹,

Rest²,

Burghouts³

et al. 2014

Tijdschrift Voor Veiligheid

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“…Person re-identification is an active research field [14][16] [18], with several recent developments [1][2] [24]. The reidentification engine can be used to combine observations of multiple operators or multiple (explosive) detectors to obtain a merged and fused result [7], and it can be used to search people and track them.…”

Section: Re-identification Enginementioning

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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“…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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Reference-based person re-identification

Cited by 65 publications

References 10 publications

Automatische gedragsanalyse voor effectiever cameratoezicht in de openbare ruimte

Automatische gedragsanalyse voor effectiever cameratoezicht in de openbare ruimte

Finding suspects in multiple cameras for improved railway protection

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

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