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Fingertip Interaction Metrics Correlate with Visual and Haptic Perception of Real Surfaces

机译:指尖互动指标与真实表面的视觉和触觉感知相关

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Both vision and touch contribute to the perception of real surfaces. Although there have been many studies on the individual contributions of each sense, it is still unclear how each modality's information is processed and integrated. To fill this gap, we investigated the similarity of visual and haptic perceptual spaces, as well as how well they each correlate with fingertip interaction metrics. Twenty participants interacted with ten different real surfaces from the Penn Haptic Texture Toolkit by either looking at or touching them and judged their similarity in pairs. By analyzing the resulting similarity ratings using non-metric multi-dimensional scaling (NMDS), we found that surfaces are similarly organized within the three-dimensional perceptual spaces of both modalities. Also, between-participant correlations were significantly higher in the haptic condition. In a separate experiment, we obtained the contact forces and accelerations acting on one finger interacting with each surface in a controlled way. We analyzed the collected fingertip interaction data in both the time and frequency domains. Our results suggest that the three perceptual dimensions for each modality can be represented by roughness/smoothness, hardness/softness, and friction, and that these dimensions can be estimated by surface vibration power, tap spectral centroid, and kinetic friction coefficient, respectively.
机译:视觉和触摸都有助于感知真实表面。尽管已经对每种感觉的个体贡献进行了许多研究,但仍不清楚如何处理和整合每种模态的信息。为了填补这一空白,我们研究了视觉和触觉感知空间的相似性,以及它们与指尖交互指标之间的关联程度。二十名参与者通过查看或触摸它们与Penn Haptic Texture Toolkit中的十种不同的真实表面进行了交互,并成对地判断了它们的相似性。通过使用非度量多维标度(NMDS)分析所得的相似度等级,我们发现表面在两种模态的三维感知空间内都相似地组织。同样,在触觉条件下,参与者之间的相关性显着更高。在一个单独的实验中,我们获得了以受控方式作用于与每个表面相互作用的一根手指上的接触力和加速度。我们分析了在时域和频域中收集的指尖交互数据。我们的结果表明,每个模态的三个感知维度可以用粗糙度/平滑度,硬度/柔软度和摩擦表示,并且这些维度可以分别通过表面振动功率,振实频谱质心和动摩擦系数来估计。

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