Suspiciousness perception in dynamic scenes: a comparison of CCTV operators and novices

Abstract

Perception of scenes has typically been investigated by using static or simplified visual displays. How attention is used to perceive and evaluate dynamic, realistic scenes is more poorly understood, in part due to the problem of comparing eye fixations to moving stimuli across observers. When the task and stimulus is common across observers, consistent fixation location can indicate that that region has high goal-based relevance. Here we investigated these issues when an observer has a specific, and naturalistic, task: closed-circuit television (CCTV) monitoring. We concurrently recorded eye movements and ratings of perceived suspiciousness as different observers watched the same set of clips from real CCTV footage. Trained CCTV operators showed greater consistency in fixation location and greater consistency in suspiciousness judgements than untrained observers. Training appears to increase between-operators consistency by learning "knowing what to look for" in these scenes. We used a novel "Dynamic Area of Focus (DAF)" analysis to show that in CCTV monitoring there is a temporal relationship between eye movements and subsequent manual responses, as we have previously found for a sports video watching task. For trained CCTV operators and for untrained observers, manual responses were most highly related to between-observer eye position spread when a temporal lag was introduced between the fixation and response data. Several hundred milliseconds after between-observer eye positions became most similar, observers tended to push the joystick to indicate perceived suspiciousness. Conversely, several hundred milliseconds after between-observer eye positions became dissimilar, observers tended to rate suspiciousness as low. These data provide further support for this DAF method as an important tool for examining goal-directed fixation behavior when the stimulus is a real moving image.

Keywords: expertise; eye movements; scene perception; security and human factors; visual search.

Figure 1

DAF analysis for untrained observers. The maximally negative correlation was obtained at a lag of 580 ms i.e., the eyes led manual responses by a lag of just over half a second. Error bars represent standard errors obtained by bootstrapping.

Figure 2

DAF analysis for trained observers. The maximally negative correlation was obtained at a lag of 2180 ms i.e., the eyes led manual responses by a lag of just over two seconds. Error bars represent standard errors obtained by bootstrapping.

Figure 3

The relationship between convergence period duration and ratings of perceived suspiciousness for untrained observers.

Figure 4

The relationship between convergence period duration and ratings of perceived suspiciousness for trained CCTV operators.