The effects of colour complexity and similarity on multiple object tracking performance

Abstract

Surface features can be used during multiple object tracking (MOT). Previous studies suggested that surface features might be stored in visual working memory to assist object tracking, and attentive tracking and visual working memory share common attentional resources. However, it is still unknown whether features of both the target and distractor sets will be stored, or features of the target and distractor sets are processed differently. Moreover, how feature distinctiveness and similarity between the target and distractor sets affect tracking and allocation of attentional resources are still not clear. First, we manipulated the colour complexity of the target set (CT) and the colour complexity of the distractor set (CD), respectively, in two experiments, where colours of the target and distractor sets were always distinct, to test their effects on tracking performance. If features of the target and distractor sets are stored, manipulating feature complexity of the target and distractor sets would significantly affect tracking performance. Second, this study tested whether tracking performance was affected by different levels of distinctiveness between the target and distractor sets (DTD) and explored how distinctiveness affected tracking and allocation of attentional resources. Results showed that DTD and CT significantly affect tracking performance and allocation of attentional resources, but not CD. These results indicated that when targets and distractors have distinct features, only the surface features of the targets are maintained in visual working memory. And when targets have the same colour with the distractors, they are more difficult and consume more attentional resources to track.

Multiple-target tracking in human and machine vision

“…Participants use a strategy for tracking to set up a competition between the two types of perceptual grouping: grouping on the basis of attentional set (tracking targets versus nontargets) and grouping on the basis of surface features (red objects versus green objects and so on). This was also reported in [54]: When targets and distractors have distinct features, only surface features of targets are maintained in visual working memory; when targets have the same color as distractors, they are more difficult and consume more attentional resources to track.…”

How Do Humans Perform in Multiple Object Tracking With Unstable Features

“…When targets were grouped with distractors automatically based on the same feature, however, the tracking performance was significantly impaired. Wang et al (2019) further demonstrated that the tracking performance could be affected by different levels of feature distinctiveness between the target and distractor sets. Finally, the feature complexity of the objects could affect attentive tracking.…”

“…Recently, many studies have demonstrated that objects’ surface features could affect attentive tracking in different ways ( Horowitz et al, 2007 ; Howard and Holcombe, 2008 ; Makovski and Jiang, 2009 ; Erlikhman et al, 2013 ; Wang et al, 2016 , 2019 ; Meyerhoff et al, 2017 ). First, objects’ unique features could facilitate attentive tracking.…”

“…Finally, the feature complexity of the objects could affect attentive tracking. Wang et al (2019) manipulated the number of colors to define the feature complexity of the target set and the distractor set. They found that only the feature complexity of the target set rather than of the distractor set could significantly affect tracking performance.…”

“…Therefore, studies of feature changes could help to reach a better understanding of how unstable features play a role in real-world attentive tracking. Previous studies provided evidence that the stable features of objects were coded and stored in visual working memory (VWM) during multiple objects attentive tracking ( Makovski and Jiang, 2009 ; Meyerhoff et al, 2017 ; Wang et al, 2019 ). The exploration of unstable features, therefore, inevitably involves the function of VWM maintenance.…”