Uncovering Activity and Patterns in Video using Slit-Tear Visualizations
Anthony Tang, Joel Lanir, Saul Greenberg, and Sid Fels. (2008). Uncovering Activity and Patterns in Video using Slit-Tear Visualizations. Department of Computer Science, University of British Columbia, Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z4.
In prior work, we introduced a visualization technique for analyzing fixed position video streams called slit-tear visualizations. This technique supports exploratory data analysis by interactively generating views about the video stream that can provide insight into the spatial/temporal relationships of the entities contained within. These insights are necessarily grounded in context of the specific video being analyzed, and in this paper, we provide a general typology of the kinds of slit-tears an analyst may use. Further, we discuss the kinds of analytic primitives that often signal relevant events given these slit-tear types. The work is relevant to human-centered computing because the technique provides the most insight in the presence of human interpretation.
video analysis, exploratory data analysis, information visualization, video history