Abstract
ABSTRACTTracking unexpected warning vehicles is required for quick response to security incident. To realize real-time vehicle tracking in a large-scale video surveillance network, a geospatial and temporal connection (GSTC) model is introduced to model the connection between videos. The transition time between videos is modeled by a Gaussian mixture model (GMM). With the developed plug-ins based on GSTC and GMM, the video streams of defined geospatial neighbors are automatically called in with the video stream that the object appears in during the tracking process. Experiments show that the ratio of success of real-time tracking is largely increased.
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