Understanding an audience's behavior is an important aspect of evaluating display installations. In particular, it is important to understand how people move around in the vicinity of displays, including viewer transitions from noticing a display, through approach, to final use of the display. Despite the importance of measuring viewer mobility patterns, there are still relatively few low-cost tools that can be used with research display deployments to capture detailed spatial and temporal behavior of an audience. In this paper, we present an approach to audience monitoring that uses an off-the-shelf depth sensor and open source computer vision algorithms to monitor the space in front of a digital display, tracking presence and movements of both passers-by and display users. We believe that our approach can help display researchers evaluate their public display deployments and improve the level of quantitative data underpinning our field.
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