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Poster

Recognition of symmetric 3D objects

MPG-Autoren
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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Vetter, T., Poggio, T., & Bülthoff, H. (1993). Recognition of symmetric 3D objects. Poster presented at Annual Meeting of the Association for Research in Vision and Ophthalmology (ARVO 1993), Sarasota, FL, USA.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-ED9C-3
Zusammenfassung
Purpose: Our ability to detect bilateral and skewed symmetry is well known. We provide evidence on psychophysical and theoretical grounds that this ability facilitates recognition of symmetric 3D objects. Methods: In psychophysical experiments with 25 paid subjects we tested recognition performance for novel views of 80 shaded wire objects shown previously only from a single view. Generalization fields were plotted by measuring recognition hit rate in horizontal, vertical and oblique directions on the viewing sphere. Results: In a first experiment we compared recognition of symmetric objects with nonsymmetric objects. The generalization ability from a given "model" view of an object to novel viewing directions (range ±90°) increased from 64 average recognition rate for nonsymmetric objects to 77 for symmetric objects. In additional experiments on viewpoint generalization for symmetric objects we found several peaks in the generalization fields. These findings are consistent with our theoretical results on recognition of bilaterally symmetric objects. The peaks observed in the generalization fields of symmetric objects are predicted by the "virtual views" (that can be generated by exploting the symmetry property) together with a network model that successfully accounts for human recognition of generic 3D objects. Conclusions: The agreement of the experimental results with the theoretical predictions support the assumption that our visual system is capable of exploiting symmetry as prior information in object recognition.