Importance of detection for video surveillance applications

Javier Varona; Jordi Gonzalez; Ignasi Rius; Juan Jose Villanueva

doi:10.1117/1.2965548

1 August 2008 Importance of detection for video surveillance applications

Javier Varona, Jordi Gonzalez, Ignasi Rius, Juan Jose Villanueva

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Optical Engineering, Vol. 47, Issue 8, 087201 (August 2008). https://doi.org/10.1117/1.2965548

Abstract

Though it is the first step of a real video surveillance application, detection has received less attention than tracking in research on video surveillance. We show, however, that the majority of errors in the tracking task are due to wrong detection. We show this by experimenting with a multi object tracking algorithm based on a Bayesian framework and a particle filter. This algorithm, which we have named iTrack, is specifically designed to work in practical applications by defining a statistical model of the object appearance to build a robust likelihood function. Likewise, we present an extension of a background subtraction algorithm to deal with active cameras. This algorithm is used in the detection task to initialize the tracker by means of a prior density. By defining appropriate performance metrics, the overall system is evaluated to elucidate the importance of detection for video surveillance applications.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Javier Varona, Jordi Gonzalez, Ignasi Rius, and Juan Jose Villanueva "Importance of detection for video surveillance applications," Optical Engineering 47(8), 087201 (1 August 2008). https://doi.org/10.1117/1.2965548

Published: 1 August 2008

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