Perceptual representations of parametrically-defined and natural objects comparing vision and haptics

Studies concerning how the brain might represent objects by means of a perceptual space have primarily focused on the visual domain. Here we want to show that the haptic modality can equally well recover the underlying structure of a physical object space, forming a perceptual space that is highly congruent to the visual perceptual space. By varying three shape parameters a physical shape space of shell-like objects was generated. Sighted participants explored pictures of the objects while blindfolded participants haptically explored 3D printouts of the objects. Similarity ratings were performed and analyzed using multidimensional scaling (MDS) techniques. Visual and haptic similarity ratings highly correlated and resulted in very similar visual and haptic MDS maps. To investigate to which degree these results are transferrable to natural objects, we performed the same visual and haptic similarity ratings and multidimensional scaling analyses using a set of natural sea shells. Again, we found very similar perceptual spaces in the haptic and visual domain. Our results suggest that the haptic modality is capable of surprisingly acute processing of complex shape.

[1]  S. Edelman,et al.  Representation of object similarity in human vision: psychophysics and a computational model , 1998, Vision Research.

[2]  R. Klatzky,et al.  Similarity of Tactual and Visual Picture Recognition with Limited Field of View , 1991, Perception.

[3]  R. Shepard,et al.  Toward a universal law of generalization for psychological science. , 1987, Science.

[4]  E. Gentaz,et al.  The visuo-haptic and haptic exploration of letters increases the kindergarten-children's understanding of the alphabetic principle , 2004 .

[5]  P. Groenen,et al.  Modern multidimensional scaling , 1996 .

[6]  Przemyslaw Prusinkiewicz,et al.  Modeling seashells , 1992, SIGGRAPH.

[7]  D G Pelli,et al.  The VideoToolbox software for visual psychophysics: transforming numbers into movies. , 1997, Spatial vision.

[8]  Carl von Linné Systema Naturae: Per Regna Tria Naturae, Secundum Classes, Ordines, Genera, Species, Cum Characteribus, Differentiis, Synonymis, Locis, , 2011 .

[9]  R L Klatzky,et al.  Identifying objects by touch: An “expert system” , 1985, Perception & psychophysics.

[10]  H. Bülthoff,et al.  Multimodal similarity and categorization of novel, three-dimensional objects , 2007, Neuropsychologia.

[11]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[12]  R. Shepard The analysis of proximities: Multidimensional scaling with an unknown distance function. I. , 1962 .

[13]  R. Shepard The analysis of proximities: Multidimensional scaling with an unknown distance function. II , 1962 .

[14]  S Lakatos,et al.  Haptic form perception: Relative salience of local and global features , 1999, Perception & psychophysics.

[15]  S Edelman,et al.  Effects of parametric manipulation of inter-stimulus similarity on 3D object categorization. , 1999, Spatial vision.

[16]  R. Klatzky,et al.  Visual mediation and the haptic recognition of two-dimensional pictures of common objects , 1990, Perception & psychophysics.

[17]  M. Ernst,et al.  Humans integrate visual and haptic information in a statistically optimal fashion , 2002, Nature.

[18]  R. Shepard Perceptual-cognitive universals as reflections of the world , 1994, Psychonomic bulletin & review.