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Using Multidimensional Scaling to Quantify the Fidelity of Haptic Rendering of Deformable Objects

MPG-Autoren
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Cooke,  T
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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Ernst,  MO
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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Eurohaptics-2006-Leskovsky.pdf
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Zitation

Leskovsky, P., Cooke, T., Ernst, M., & Harders, M. (2006). Using Multidimensional Scaling to Quantify the Fidelity of Haptic Rendering of Deformable Objects. In A. Kheddar, & B. Bayart (Eds.), EuroHaptics International Conference (EH 2006) (pp. 289-295). Paris, France.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-D0FD-0
Zusammenfassung
In this paper, we examine the application of a psychophysical evaluation technique to quantify the fidelity of haptic rendering methods. The technique is based on multidimensional scaling (MDS) analysis of similarity ratings provided by users comparing pairs of
haptically-presented objects. Unbeknownst to the participants, both real and virtual deformable objects were presented to them. In addition, virtual objects were either presented under higher-fidelity rendering condition or under lower-fidelity condition in which force filtering and proxy-point filtering were removed. We hypothesized
that reducing fidelity of virtual rendering would exaggerate the difference between real and virtual objects. MDS analysis of pairwise similarity data provided quantitative confirmation that users perceived a clear difference between real and virtual objects in the
lower-fidelity, but not in the higher-fidelity condition. In the latter, a single perceptual dimension, corresponding to stiffness, sufficed to explain similarity data, while two perceptual dimensions were needed in the former condition. This study demonstrates how MDS analysis provides an opportunity to visualize and quantify the perceptual effects of changes in rendering parameters and how it can be used in the evaluation of haptic rendering scenarios.