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Abstract:
There is a large amount of movements in the environment but only some are relevant to an observer, as these indicate objects of interest (e.g., prey or predator). In a previous study, we
found an advantage for detecting dynamic targets (e.g., humans) compared to static ones in
visually degraded natural scenes. Here we used a visual search paradigm to investigate the
role of motion in the perception of natural scenes across different target categories and without
image degradation. Observers were presented with a circular array of 2, 4, 6 or 8 natural scene
movies. These scenes were selected from three categories: human actions, animal movements,
and machine movements. The objects in these different categories differed in their shape and
movement patterns. The observers’ task was to search for a target category among distractors
from another category. In Experiment 1, observers searched for human targets among machine
distractors on one block and machine targets among human distractors on another block. The
block order was counterbalanced across observers. In Experiment 2, we used animals and
machines in the same design. Lastly, in Experiment 3, we used humans and animals. Across
all experiments, search times were affected by set size. Importantly, we found that observers
were faster at searching for humans and animals among machines than they were at searching
for machines among either of these distractor categories (Experiments 1 and 2), suggesting
that biological motion facilitated search. However, there was no difference in search times for
humans and animals (Experiment 3), suggesting that human and animal movements are treated
equivalently by the visual system. Overall, the present results point to the importance of a
high-level interpretation of motion (e.g., as biological versus mechanical motion) in processing
natural scenes.
