Impact of video content and resolution on the cognitive dynamics of surveillance decision-making

Security screeners identify targets from surveillance videos. Their performance can fluctuate as resolution or video content salience varies. Image spatial resolution may be degraded if a camera has low pixel density. Similarly, temporal resolution can be degraded due to transmission interference or low bandwidth. Both types of deteriorated resolution can increase observer uncertainty and reduce target identification accuracy. Further, these outcomes may reflect an interaction between target type and resolution. To help quantify, study, and explain possible interactions, we utilize process-tracing methodology to understand the cognitive dynamics of surveillance decisions. These insights can improve the development of surveillance augmentation technologies and processes. Mouse tracking is a robust process-tracing method successfully leveraged to observe continuously unfolding cognitive processes. Lateral vacillating mouse movements reflect decision uncertainty, and trajectory curvature serves measures cognitive conflict to select an unchosen alternative. We utilized mouse tracking to measure decision conflict during a video surveillance task with varying salience due to resolution or target type. Greater cognitive conflict was found when observers classified person-related targets compared to vehicle-related targets. Trajectories indicated stronger certainty when classifying events as having occurred, rather than when indicating events did not occur. Greater cognitive conflict was seen under degraded spatial resolution when observers were moderately confident compared to strongly confident or reported themselves as guessing. Under degraded temporal resolution, the greatest cognitive conflict occurred when observers reported they were guessing. Beyond these findings, we have demonstrated the viability of mouse tracking as an unobtrusive process-tracing method for measuring uncertainty during realistic surveillance.