Abstract

The goal of the present study was to examine whether intention type affects eye movement patterns in a change detection task In addition, we assessed whether the eye movement index could be used to identify human implicit intent. We attempted to generate three types of intent amongst the study participants, dividing them into one of three conditions; each condition received different information regarding an impending change to the visual stimuli. In the “navigational intent” condition, participants were asked to look for any interesting objects, and were not given any more information about the impending change. In the “low-specific intent” condition, participants were informed that a change would occur. In the “high-specific intent” condition, participants were told that a change would occur, and that an object would disappear. In addition to this main change detection task, participants also had to perform a primary task, in which they were required to name aloud the colors of objects in the pre-change scene. This allowed us to control for the visual searching process during the pre-change scene. The main results were as follows: firstly, the primary task successfully controlled for the visual search process during the pre-change scene, establishing that there were no differences in the patterns of eye movements across all three conditions despite differing intents. Secondly, we observed significantly different patterns of eye movement between the conditions in the post-change scene, suggesting that generating a specific intent for change detection yields a distinctive pattern of eye-movements. Finally, discriminant function analysis showed a reasonable classification rate for identifying a specific intent. Taken together, it was found that both participant intent and the specificity of information provided to the participants affect eye movements in a change detection task.

Highlights

  • Our everyday visual environment consists of many objects, with a wide variety of characteristics

  • Participants in all three conditions were required to perform the primary task before carrying out the change detection task, in order to control the participants’ search processes

  • The effects on fixation count [F (2, 411) = .725, p = .485, ns.], the first fixation duration [F (2, 411) = .181, p = .834, ns.], the mean fixation duration [F (2, 411) = .415, p = .661, ns.], and the total fixation duration [F (2, 411) = .510, p = .601, ns.] were not significant. These results suggest that the primary task effectively controlled the visual searching process during pre-change scene

Read more

Summary

Introduction

Our everyday visual environment consists of many objects, with a wide variety of characteristics. The visual environment can undergo various physical transformations. These dynamic transformations usually result in perceptible changes in the scene. A number of researchers have found that people are surprisingly poor at detecting changes in visual scenes. These failures of change detection were observed both in complex natural scenes and in artificial displays, and regardless of whether or not observers were expecting the change (Rensink, 2002; Simons & Levin, 1997)

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call