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Everett Mettler, Gennady Erlikhman, Brian Keane, Todd Horowitz, Philip Kellman; Further evidence for automatic, feature-based grouping in multiple object tracking. Journal of Vision 2012;12(9):458. doi: https://doi.org/10.1167/12.9.458.
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Background: In a multiple object tracking task, if half the targets and half the distractors share a common feature, and remaining objects share an alternate feature, tracking performance is impaired relative to a condition in which all objects share the same features (Mettler et al., 2011). Tracking decrements appear to be due to automatic perceptual grouping. However, an alternative hypothesis is that the heterogeneity of target features impairs tracking, independent of distractor features. According to this hypothesis, even if distractor features are changed so that targets cannot group with distractors, tracking performance should continue to be poor. Method: To consider this possibility, we compared two grouping conditions for 4 different features: color, shape, size and all features combined. In both conditions, two of four targets possessed one grouping feature (e.g. red in the color condition) and two possessed an alternate feature (e.g. green). In a ‘Sharing’ condition, distractors possessed the same features in the same distribution. In a ‘Diversity’ condition, distractors possessed two features not present in the targets (e.g. yellow and purple). One target and one distractor (always distinct featurally) were presented in each screen quadrant. After targets flashed briefly, each pair orbited a central point within its respective quadrant. Participants attempted to identify each target with a mouse. Results: Overall performance was worse for the Sharing condition than for the Diversity condition (p<.001). This comparison was significant for all features except size (p = .066). Conclusion: Superior tracking in the Diversity condition argues that previously observed tracking decrements in feature sharing conditions cannot be ascribed to the effects of feature diversity. These findings support our hypothesis that shared features lead to automatic feature-based grouping between targets and distractors.
Meeting abstract presented at VSS 2012
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