Video Visual Analytics of Tracked Moving Objects

Exploring video data by simply watching does not scale for large databases. Especially, this problem becomes obvious in the field of video surveillance. Motivated by a mini challenge of the contest of the IEEE Symposium on Visual Analytics Science and Technology 2009 (Detecting the encounter of persons in a provided video stream utilizing the techniques of visual analytics), we propose an approach for fast identification of relevant objects based on the properties of their trajectories. We present a novel visual and interactive filter process for fast video exploration that yields good results even with challenging video data. The video material includes changing illumination and was captured with low temporal resolution by a camera panning between different views.