How Do Humans Perform in Multiple Object Tracking With Unstable Features.

Chen Zhao,Liuqing Wei,Chundi Wang,Bin Hu,Xuemin Zhang,Xiaowei Li,Luming Hu

doi:10.3389/fpsyg.2020.01940

Abstract

In real-world scenarios, objects’ surface features sometimes change as they move, impairing the continuity of objects. However, it is still unknown how our visual system adapts to this dynamic change. Hence, the present study investigated the role of feature changes in attentive tracking through a modified multiple object tracking (MOT) task. The feature heterogeneity and feature stability were manipulated in two experiments. The results from Experiment 1 showed that the tracking performance under feature-changed condition was lower than that under the feature-fixed condition only when the objects were four colors grouped or all unique, suggesting that the performance decrease was moderated by the feature heterogeneity. In Experiment 2, we further examined this effect by manipulating the frequency of feature change. The results showed that when the target set was one color or two colors grouped (the color grouping for the distractor set corresponded with it), the tracking performance decreased significantly as the feature-change frequency increased. However, this trend was not the case when the objects were of the same color or eight unique colors. In addition, a relatively consistent effect appeared both in Experiments 1 and 2. When objects have unique features, the tracking performance decreased significantly as the increase of feature heterogeneity in each frequency of feature changes. Taken together, we concluded that unstable features could be utilized in attentive tracking, and the extent to which the observers relied on surface feature information to assist tracking depended on the level of feature heterogeneity and the frequency of feature change.

Highlights

How humans assign visual attentional resources in multifocal dynamic scenes has typically been studied using the multiple object tracking (MOT) task (Pylyshyn and Storm, 1988)
The interaction effect between feature consistency and feature heterogeneity was significant, F(3, 69) = 16.48, p < 0.001, η2p = 0.42. This finding suggested that the effect of feature consistency on tracking performance could be significantly regulated by the different levels of feature heterogeneity
Simple effect test (Bonferroni correction) was calculated to analyze the detailed differences among the four feature heterogeneity conditions in each feature consistency condition, and the detailed differences between the two feature consistency conditions in each feature heterogeneity condition. For the former, the results showed that both the eight-unique condition [t(23) = 4.34, p < 0.001, Cohen’s d = 0.82] and the four-unique condition [t(23) = 6.91, p < 0.001, Cohen’s d = 1.36] resulted in a significant impairment related to the feature change, while the two-unique condition [t(23) = 2.05, p = 0.052, Cohen’s d = 0.42] and the homogeneous condition [t(23) = 0.49, p = 0.625, Cohen’s d = 0.09] did not. It suggested that the change of feature did not always undermine tracking performance and the actual effect depended on the level of feature heterogeneity

Summary

Introduction

How humans assign visual attentional resources in multifocal dynamic scenes has typically been studied using the multiple object tracking (MOT) task (Pylyshyn and Storm, 1988). Objects’ surface features seemed to be poorly retained in attentive tracking and had little effect on the establishment and maintenance of object continuity. These studies might have underestimated the importance of objects’ features, since the objects in these experiments were all identical, which made it helpless for the observers to use them to assist with tracking (Makovski and Jiang, 2009)

Methods

Results

Conclusion