182 research outputs found

    Haptic object individuation

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    Plaisier M, Bergmann Tiest WM, Kappers AML. Haptic object individuation. IEEE Transactions on Haptics. 2010;3(4):257-265

    Haptic search for spheres and cubes

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    Plaisier M, Bergmann Tiest WM, Kappers AML. Haptic search for spheres and cubes. In: Ferre M, ed. Haptics: Perception, devices and scenarios. Lecture notes in computer science. Vol 5024 of Lecture Notes on Computer Science. Berlin, Heidelberg: Berlin/Heidelberg: Springer; 2008: 275-282

    The role of item fixation in haptic search

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    Plaisier M, Kuling IA, Bergmann Tiest WM, Kappers AML. The role of item fixation in haptic search. In: Institute of Electrical and Electronics Engineers, ed. Third Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. Piscataway, NJ: IEEE; 2009: 417-421

    The shape-weight illusion

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    In the present experiment, we investigated the influence of the shape of 3-dimensional objects on haptic perception of weight. A systematic shape-weight illusion was found when subjects compared a tetrahedron to a cube: a cube was perceived as being heavier than a tetrahedron of the same physical mass and volume. However, when subjects compared a sphere to a tetrahedron or to a cube, some subjects perceived the sphere as heavier than the other objects, while other subjects perceived the sphere as being lighter. These results indicate that the influence of shape on haptic perception of weight is not mediated only by the perceived volume, as would be predicted from previous studies, but that some subject dependent factors are involved

    Parallel processing of shape and texture in haptic search

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    In a haptic search task, one has to determine the presence of a target among distractors. It has been shown that if the target differs from the distractors in two properties, shape and texture, performance is better than in both single-property conditions (Van Polanen, Bergmann Tiest, & Kappers, 2013). The search for a smooth sphere among rough cubical distractors was faster than both the searches for a rough sphere (shape information only) and for a smooth cube (texture information only). This effect was replicated in this study as a baseline. The main focus here was to further investigate the nature of this integration. It was shown that performance is better when the two properties are combined in a single target (smooth sphere), than when located in two separate targets (rough sphere and smooth cube) that are simultaneously present. A race model that assumes independent parallel processing of the two properties could explain the enhanced performance with two properties, but this could only take place effectively when the two properties were located in a single target. © 2014 Elsevier B.V
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