Visual and Haptic Representations of Material Properties

In: Multisensory Research
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  • 1 Abteilung Allgemeine Psychologie, Universität Gießen, 35394 Gießen, Germany

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Research on material perception has received an increasing amount of attention recently. Clearly, both the visual and the haptic sense play important roles in the perception of materials, yet it is still unclear how both senses compare in material perception tasks. Here, we set out to investigate the degree of correspondence between the visual and the haptic representations of different materials. We asked participants to both categorize and rate 84 different materials for several material properties. In the haptic case, participants were blindfolded and asked to assess the materials based on haptic exploration. In the visual condition, participants assessed the stimuli based on their visual impressions only. While categorization performance was less consistent in the haptic condition than in the visual one, ratings correlated highly between the visual and the haptic modality. PCA revealed that all material samples were similarly organized within the perceptual space in both modalities. Moreover, in both senses the first two principal components were dominated by hardness and roughness. These are two material features that are fundamental for the haptic sense. We conclude that although the haptic sense seems to be crucial for material perception, the information it can gather alone might not be quite fine-grained and rich enough for perfect material recognition.

  • Amedi A., Jacobson G., Hendler T., Malach R., Zohary E. (2002). Convergence of visual and tactile shape processing in the human lateral occipital complex, Cereb. Cortex 12, 12021212.

    • Search Google Scholar
    • Export Citation
  • Amedi A., von Kriegstein K., van Atteveldt N. M., Beauchamp M. S., Naumer M. J. (2005). Functional imaging of human crossmodal identification and object recognition, Exp. Brain Res. 166, 559571.

    • Search Google Scholar
    • Export Citation
  • Bergmann Tiest W. M., Kappers A. M. L. (2007). Haptic and visual perception of roughness, Acta Psychol. 124, 177189.

  • Bhushan N., Rao A. R., Lohse G. L. (1997). The texture lexicon: Understanding the categorization of visual texture terms and their relationship to texture images, Cognit. Sci. 21, 219246.

    • Search Google Scholar
    • Export Citation
  • Brodatz P. (1966). Textures. Dover, New York, NY, USA.

  • Buckingham G., Cant J. S., Goodale M. A. (2009). Living in a material world: How visual cues to material properties affect the way that we lift objects and perceive their weight, J. Neurophysiol. 102, 31113118.

    • Search Google Scholar
    • Export Citation
  • Cant J. S., Goodale M. A. (2011). Scratching beneath the surface: New insights into the functional properties of the lateral occipital area and parahippocampal place area, J. Neurosci. 31, 82488258.

    • Search Google Scholar
    • Export Citation
  • Cooke T., Jäkel F., Wallraven C., Bulthoff H. H. (2007). Multimodal similarity and categorization of novel, three-dimensional objects, Neuropsychologia 45, 484495.

    • Search Google Scholar
    • Export Citation
  • Fleming R. W. (2012). Human perception: Visual heuristics in the perception of glossiness, Curr. Biol. 22, 865866.

  • Fleming R. W., Dror R. O., Adelson E. H. (2003). Real-world illumination and the perception of surface reflectance properties, J. Vision 3(5), 3.

    • Search Google Scholar
    • Export Citation
  • Fleming R. W., Wiebel C. B., Gegenfurtner K. R. (2013). Perceptual qualities and material classes, J. Vision 13(8), 9.

  • Gaissert N., Bülthoff H. H., Wallraven C. (2011). Similarity and categorization: From vision to touch, Acta Psychol. 138, 219230.

  • Gaissert N., Wallraven C. (2012). Categorizing natural objects: A comparison of the visual and the haptic modalities, Exp. Brain Res. 216, 123134.

    • Search Google Scholar
    • Export Citation
  • Gaissert N., Wallraven C., Bülthoff H. H. (2010). Visual and haptic perceptual spaces show high similarity in humans, J. Vision 10(11), 2.

    • Search Google Scholar
    • Export Citation
  • Ged G., Obein G., Silvestri Z., Le Rohellec J., Viénot F. (2010). Recognizing real materials from their glossy appearance, J. Vision 10(9), 18.

  • Giesel M., Gegenfurtner K. R. (2010). Color appearance of real objects varying in material, hue and shape, J. Vision 10(9), 10.

  • Hiramatsu C., Goda N., Komatsu H. (2011). Transformation from image-based to perceptual representation of materials along the human ventral visual pathway, Neuroimage 57, 482494.

    • Search Google Scholar
    • Export Citation
  • Ho Y.-X., Landy M. S., Maloney L. T. (2006). How direction of illumination affects visually perceived surface roughness, J. Vision 6(5), 9.

    • Search Google Scholar
    • Export Citation
  • Hollins M., Bensmaïa S., Karlof K., Young F. (2000). Individual differences in perceptual space for tactile textures: evidence from multidimensional scaling, Percept. Psychophys. 62, 15341544.

    • Search Google Scholar
    • Export Citation
  • Hollins M., Faldowski R., Rao S., Young F. (1993). Perceptual dimensions of tactile surface texture: a multidimensional scaling analysis, Percept. Psychophys. 54, 697705.

    • Search Google Scholar
    • Export Citation
  • Kim J., Anderson B. L. (2010). Image statistics and the perception of surface gloss and lightness, J. Vision 10(9), 3.

  • Lederman S. J., Abbott S. G. (1981). Texture perception: studies of intersensory organization using a discrepancy paradigm and visual versus tactual psychophysics, J. Exp. Psychol. 7, 902915.

    • Search Google Scholar
    • Export Citation
  • Liu C., Sharan L., Adelson E. H., Rosenholtz R. (2010). Exploring features in a Bayesian framework for material recognition, Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference, San Francisco, CA, pp. 239–246.

  • Motoyoshi I. (2010). Highlight-shading relationship as a cue for the perception of translucent and transparent materials, J. Vision 10, 6.

    • Search Google Scholar
    • Export Citation
  • Motoyoshi I., Nishida S., Sharan L., Adelson E. H. (2007). Image statistics and the perception of surface qualities, Nature 447, 206209.

  • Okamoto S., Nagano H., Yamada Y. (2013). Psychophysical dimensions of tactile perception of textures, J. IEEE Trans. Haptics 6, 8193.

  • Olkkonen M., Brainard D. H. (2010). Perceived glossiness and lightness under real-world illumination, J. Vision 10, 5.

  • Olkkonen M., Witzel C., Hansen T., Gegenfurtner K. R. (2010). Categorical color constancy for real surfaces, J. Vision 10(9), 16.

  • Picard D., Dacremont C., Valentin D., Giboreau A. (2003). Perceptual dimensions of tactile textures, Acta Psychol. 114, 165184.

  • Rao A. R., Lohse G. L. (1996). Towards a texture naming system: Identifying relevant dimensions of texture, Vision Res. 36, 16491669.

    • Search Google Scholar
    • Export Citation
  • Sharan L., Rosenholtz R., Adelson E. H. (2009). What can you see in a brief glance? J. Vision 9, 784.

  • Stilla R., Sathian K. (2008). Selective visuo-haptic processing of shape and texture, Hum. Brain Mapp. 29, 11231138.

  • Whitaker T. A., Simões-Franklin C., Newell F. N. (2008). Vision and touch: Independent or integrated systems for the perception of texture? Brain Res. 1242, 5972.

    • Search Google Scholar
    • Export Citation
  • Wiebel C. B., Valsecchi M., Gegenfurtner K. R. (2013). The speed and accuracy of material recognition in natural images, Atten. Percept. Psychophys. 75, 954966.

    • Search Google Scholar
    • Export Citation

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