Surveillance Video Querying With A Human-in-the-Loop

2020-06-19
STONEBROKER, MICHAEL
Bhargava, Bharat
Cafarella, Michael
COLLINS, ZACHARY
McClellan, Jenna
SIPSER, AARON
Sun, Tao
NESEN, ALİNA
SOLAIMAN, K.M.A.
MANI, GANAPATHY
Kochpatcharin, Kevin
Kochpatcharin, Kevin
Angın, Pelin
MACDONALD, JAMES
SurvQ is a video monitoring system appropriate for surveillance applications such as those found in security and law enforcement. It performs real time object property identification and stores all data in a scalable DBMS. Standing queries implemented as database triggers are supported. SurvQ contains novel adaptive machine learning and algorithmic property classification. The application of SurvQ to assist the West Lafayette (IN) police department at identifying suspects in video is described. This paper also describes the basics of the SurvQ architecture and its human-in-the-loop interface designed to accelerate everyday police investigations.
Workshop on Human-In-the-Loop Data Analytics (HILDA)

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Citation Formats
M. STONEBROKER et al., “Surveillance Video Querying With A Human-in-the-Loop,” presented at the Workshop on Human-In-the-Loop Data Analytics (HILDA), Amerika Birleşik Devletleri, 2020, Accessed: 00, 2022. [Online]. Available: https://hilda.io/2020/proceedings/HILDA2020_paper6.pdf.