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  Metrics of the perception of body movement

Giese, M., Thornton, I., & Edelman, S. (2009). Metrics of the perception of body movement. Journal of Vision, 8(9): 13, pp. 1-18. doi:10.1167/8.9.13.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-301E-6 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-301F-5
Genre: Journal Article

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Giese, MA, Author              
Thornton, I1, 2, Author              
Edelman, S, Author
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Abstract: Body movements are recognized with speed and precision, even from strongly impoverished stimuli. While cortical structures involved in biological motion recognition have been identified, the nature of the underlying perceptual representation remains largely unknown. We show that visual representations of complex body movements are characterized by perceptual spaces with well-defined metric properties. By multidimensional scaling, we reconstructed from similarity judgments the perceptual space configurations of stimulus sets generated by motion morphing. These configurations resemble the true stimulus configurations in the space of morphing weights. In addition, we found an even higher similarity between the perceptual metrics and the metrics of a physical space that was defined by distance measures between joint trajectories, which compute spatial trajectory differences after time alignment using a robust error norm. These outcomes were independent of the experimental paradigm for the assessment of perceived similarity (pairs-comparison vs. delayed match-to-sample) and of the method of stimulus presentation (point-light stimuli vs. stick figures). Our findings suggest that the visual perception of body motion is veridical and closely reflects physical similarities between joint trajectories. This implies that representations of form and motion share fundamental properties and places constraints on the computational mechanisms that support the recognition of biological motion patterns.

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 Dates: 2009-07
 Publication Status: Published in print
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 Identifiers: DOI: 10.1167/8.9.13
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Title: Journal of Vision
Source Genre: Journal
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Publ. Info: Charlottesville, VA : Scholar One, Inc.
Pages: - Volume / Issue: 8 (9) Sequence Number: 13 Start / End Page: 1 - 18 Identifier: ISSN: 1534-7362
CoNE: https://pure.mpg.de/cone/journals/resource/111061245811050