Analyzing Perceptual Representations of Complex, Parametrically-Defined Shapes Using MDS

Abstract

Abstract. In this study we show that humans are able to form a perceptual space from a complex, three-dimensional shape space that is highly congruent to the physical object space no matter if the participants explore the objects visually or haptically. The physical object space consists of complex, shell-shaped objects which were generated by varying three shape parameters. In several psychophysical experiments participants explored the objects either visually or haptically and performed similarity ratings. Multidimensional scaling (MDS) analyses showed high congruency of the visual and haptic perceptual space to the physical object space. Additionally, visual and haptic exploration resulted in very similar MDS maps providing evidence for one shared perceptual space underlying both modalities.

Visuo-haptic multisensory object recognition, categorization, and representation

“…More recently, however, a series of studies has systematically compared visual and haptic categorization. Using multi-dimensional scaling analysis, these studies showed that visual and haptic similarity ratings and categorization result in perceptual spaces [i.e., topological representations of the perceived (dis)similarity along a given dimension] that are highly congruent between modalities for novel 3-D objects ( Cooke et al, 2007 ), more realistic 3-D shell-like objects ( Gaißert et al, 2008 , 2010 , 2011 ) and for natural objects, i.e., actual seashells ( Gaißert and Wallraven, 2012 ). This was so in both unisensory and bisensory conditions ( Cooke et al, 2007 ) and whether 2-D visual objects were compared to haptic 3-D objects ( Gaißert et al, 2008 , 2010 ) or passive viewing of 2-D objects was compared to interactive viewing and active haptic exploration of 3-D objects, i.e., such that visual and haptic exploration were more similar ( Gaißert et al, 2010 ).…”

“…Using multi-dimensional scaling analysis, these studies showed that visual and haptic similarity ratings and categorization result in perceptual spaces [i.e., topological representations of the perceived (dis)similarity along a given dimension] that are highly congruent between modalities for novel 3-D objects ( Cooke et al, 2007 ), more realistic 3-D shell-like objects ( Gaißert et al, 2008 , 2010 , 2011 ) and for natural objects, i.e., actual seashells ( Gaißert and Wallraven, 2012 ). This was so in both unisensory and bisensory conditions ( Cooke et al, 2007 ) and whether 2-D visual objects were compared to haptic 3-D objects ( Gaißert et al, 2008 , 2010 ) or passive viewing of 2-D objects was compared to interactive viewing and active haptic exploration of 3-D objects, i.e., such that visual and haptic exploration were more similar ( Gaißert et al, 2010 ). These highly similar visual and haptic perceptual spaces both showed high fidelity to the physical object space [i.e., a topological representation of the actual (dis)similarity along a given dimension; Gaißert et al, 2008 , 2010 ], retaining the category structure (the ordinal adjacency relationships within the category, i.e., the actual progression in variation along a given dimension, for example from roughest to smoothest; Cooke et al, 2007 ).…”

“…This was so in both unisensory and bisensory conditions ( Cooke et al, 2007 ) and whether 2-D visual objects were compared to haptic 3-D objects ( Gaißert et al, 2008 , 2010 ) or passive viewing of 2-D objects was compared to interactive viewing and active haptic exploration of 3-D objects, i.e., such that visual and haptic exploration were more similar ( Gaißert et al, 2010 ). These highly similar visual and haptic perceptual spaces both showed high fidelity to the physical object space [i.e., a topological representation of the actual (dis)similarity along a given dimension; Gaißert et al, 2008 , 2010 ], retaining the category structure (the ordinal adjacency relationships within the category, i.e., the actual progression in variation along a given dimension, for example from roughest to smoothest; Cooke et al, 2007 ). The isomorphism between perceptual (in either modality) and physical spaces was, furthermore, task-independent, whether simple similarity rating ( Gaißert et al, 2008 ), unconstrained (free sorting), semi-constrained (making exactly three groups) or constrained (matching to a prototype object) categorization ( Gaißert et al, 2011 ).…”

“…These highly similar visual and haptic perceptual spaces both showed high fidelity to the physical object space [i.e., a topological representation of the actual (dis)similarity along a given dimension; Gaißert et al, 2008 , 2010 ], retaining the category structure (the ordinal adjacency relationships within the category, i.e., the actual progression in variation along a given dimension, for example from roughest to smoothest; Cooke et al, 2007 ). The isomorphism between perceptual (in either modality) and physical spaces was, furthermore, task-independent, whether simple similarity rating ( Gaißert et al, 2008 ), unconstrained (free sorting), semi-constrained (making exactly three groups) or constrained (matching to a prototype object) categorization ( Gaißert et al, 2011 ). As in vision, haptics also exhibits categorical perception, i.e., discriminability increases sharply when objects belong to different categories and decreases when they belong to the same category ( Gaißert et al, 2012 ).…”

Foundations of Transparency in Tactile Information Design

“…In an early use of haptic MDS, Hollins et al tested perception of 17 real tactile surface textures through sorting [30] and derived a 3D solution space; this group has also found "substantial but not complete" agreement in stimulus organization between individuals [29]. More recently, MDS has been used to measure user organization of tactile melodies [58] and complex shapes [19].…”