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  Learned non-rigid object motion is a view-invariant cue to recognizing novel objects

Chuang, L., Vuong, Q., & Bülthoff, H. (2012). Learned non-rigid object motion is a view-invariant cue to recognizing novel objects. Frontiers in Computational Neuroscience, 6: 26, pp. 1-8. doi:10.3389/fncom.2012.00026.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-B764-E Version Permalink: http://hdl.handle.net/21.11116/0000-0001-8CC7-1
Genre: Journal Article

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Chuang, LL1, 2, Author              
Vuong, QC1, 2, Author              
Bülthoff, HH1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: There is evidence that observers use learned object motion to recognize objects. For instance, studies have shown that reversing the learned direction in which a rigid object rotated in depth impaired recognition accuracy. This motion reversal can be achieved by playing animation sequences of moving objects in reverse frame order. In the current study, we used this sequence-reversal manipulation to investigate whether observers encode the motion of dynamic objects in visual memory, and whether such dynamic representations are encoded in a way that is dependent on the viewing conditions. Participants first learned dynamic novel objects, presented as animation sequences. Following learning, they were then tested on their ability to recognize these learned objects when their animation sequence was shown in the same sequence order as during learning or in the reverse sequence order. In Experiment 1, we found that non-rigid motion contributed to recognition performance; that is, sequence-reversal decreased sensitivity across different tasks. In subsequent experiments, we tested the recognition of non-rigidly deforming (Experiment 2) and rigidly rotating (Experiment 3) objects across novel viewpoints. Recognition performance was affected by viewpoint changes for both experiments. Learned non-rigid motion continued to contribute to recognition performance and this benefit was the same across all viewpoint changes. By comparison, learned rigid motion did not contribute to recognition performance. These results suggest that non-rigid motion provides a source of information for recognizing dynamic objects, which is not affected by changes to viewpoint.

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 Dates: 2012-05
 Publication Status: Published online
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 Identifiers: DOI: 10.3389/fncom.2012.00026
BibTex Citekey: ChuangVB2012_2
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Title: Frontiers in Computational Neuroscience
Source Genre: Journal
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Pages: - Volume / Issue: 6 Sequence Number: 26 Start / End Page: 1 - 8 Identifier: -