2024-03-29T04:55:41Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/304882016-02-17T03:37:54Zcom_10261_106com_10261_4col_10261_359
http://hdl.handle.net/10261/30488
10.1117/1.2965548
31105
Importance of detection for video surveillance applications
The International Society for Optics and Photonics
2008
artículo
Varona, Javier
Gonzàlez, Jordi
Rius, Ignasi
Villanueva, Juan J.
Video surveillance
Visual tracking
Target detection
2008
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.
Optical Engineering
2008
47
087201