Exploring the Need and Design for Situated Video Analytics.

Visual video analytics research, stemming from data captured by surveillance cameras, have mainly focused on traditional computing paradigms, despite emerging platforms including mobile devices. We investigate the potential for situated video analytics, which involves the inspection of video data in the actual environment where the video was captured [14]. Our ultimate goal is to explore the means to visually explore video data effectively, in situated contexts. We first investigate the performance of visual analytic tasks in situated vs. non-situated settings. We find that participants largely benefit from environmental cues for many analytic tasks. We then pose the question of how best to represent situated video data. To answer this, in a design session we explore end-users’ views on how to capture such data. Through the process of sketching, participants leveraged being situated, and explored how being in-situ influenced the participants’ integration of their designs. Based on these two elements, our paper proposes the need to develop novel spatial analytic user interfaces to support situated video analysis.