Abstract
How do featural characteristics of objects affect our ability to track them? In typical multiple object tracking experiments, observers are asked to track several identical items among identical distractors. However, in the real world, we usually track distinct objects. Can the visual system take advantage of featural differences between objects to improve tracking performance? We asked observers to track 4 of 8 gray disks for 5 seconds. In the overlapping condition, disks bounced off display boundaries but could occlude one another. In the non-overlapping condition, disks also bounced off each other. Performance was significantly lower in the overlapping condition (F (1, 7) = 8.74, p < .0001). In Exp. 2, we added color and asked observers to track 5 of 10 disks. All disks started and ended the trial as light gray. During tracking, each disk was assigned a color, and the colors changed at intervals during the trial. In the unique condition, each disk was assigned a unique color; in the identical condition, all disks were assigned the same color. There was no advantage for unique over identical conditions (F (1, 9) < 1), nor was performance in the overlapping condition helped when each item was uniquely colored (F (1, 9) < 1). Does this mean that tracking ignores color information entirely? In Exp 3. disks were grouped into two uniformly colored sets. Again, colors changed throughout the trial. In the segregated condition, tracked disks were one color and untracked disks another. In the mixed condition, color and tracked status were independent. Performance was dramatically better in the segregated condition than in the mixed condition (F (1, 9) = 40.22, p < .0001) and segregation also reduced the overlap deficit (F (1, 9) = 10.13, p < .01). We conclude that featural properties of objects can influence tracking, but only by distinguishing groups of targets from distractors, not by giving objects individual identities.