texture perception
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2021 ◽  
Vol 21 (9) ◽  
pp. 2188
Author(s):  
Kosuke Okada ◽  
Isamu Motoyoshi

2021 ◽  
Vol 21 (9) ◽  
pp. 2174
Author(s):  
Justin D. Lieber ◽  
J. Anthony Movshon

Author(s):  
Benjamin Balas

Texture perception is a rich subdomain of vision science that focuses on how the visual system encodes and interprets images that can be defined in terms of self-similarity over space. The field’s understanding of the computational and neural bases of texture perception has advanced, drawing upon key results from psychophysics, cognitive neuroscience, and visual development. The relevance of texture representations to a broader set of visual mechanisms supporting “statistical vision” is also discussed, with an emphasis on the challenges and potential rewards of studying texture perception in the context of natural stimuli and ecologically relevant tasks.


2021 ◽  
Author(s):  
Yoichi Yamazaki ◽  
Masataka Imura ◽  
Masashi Nakatani ◽  
Shin Osanai ◽  
Noriko Nagata ◽  
...  

Author(s):  
Scinob Kuroki ◽  
Masataka Sawayama ◽  
Shin'ya Nishida

Humans can haptically discriminate surface textures when there is a significant difference in the statistics of the surface profile. Previous studies on tactile texture discrimination have emphasized the perceptual effects of lower-order statistical features such as carving depth, inter-ridge distance, and anisotropy, which can be characterized by local amplitude spectra or spatial-frequency/orientation subband histograms. However, the real-world surfaces we encounter in everyday life also differ in the higher-order statistics, such as statistics about correlations of nearby spatial-frequencies/orientations. For another modality, vision, the human brain has the ability to utilize the textural differences in both higher- and lower-order image statistics. In this work, we examined whether the haptic texture perception can utilize higher-order surface statistics as visual texture perception does, by 3D-printing textured surfaces transcribed from different 'photos' of natural scenes such as stones and leaves. Even though the maximum carving depth was well above the haptic detection threshold, some texture pairs were hard to discriminate. Specifically, those texture pairs with similar amplitude spectra were difficult to discriminate, which suggests that the lower-order statistics have the dominant effect on tactile texture discrimination. To directly test the poor sensitivity of the tactile texture perception to higher-order surface statistics, we matched the lower-order statistics across different textures using a texture synthesis algorithm and found that haptic discrimination of the matched textures was nearly impossible unless the stimuli contained salient local features. We found no evidence for the ability of the human tactile system to use higher-order surface statistics for texture discrimination.


2021 ◽  
pp. 110477
Author(s):  
Andrea Aleixandre ◽  
Yaiza Benavent-Gil ◽  
Elena Velickova ◽  
Cristina M. Rosell

LWT ◽  
2021 ◽  
Vol 140 ◽  
pp. 110718
Author(s):  
P. Puerta ◽  
R. Garzón ◽  
C.M. Rosell ◽  
S. Fiszman ◽  
L. Laguna ◽  
...  

Author(s):  
Knut Drewing ◽  
Alexandra Lezkan

AbstractHaptic texture perception is based on sensory information sequentially gathered during several lateral movements (“strokes”). In this process, sensory information of earlier strokes must be preserved in a memory system. We investigated whether this system may be a haptic sensory memory. In the first experiment, participants performed three strokes across each of two textures in a frequency discrimination task. Between the strokes over the first texture, participants explored an intermediate area, which presented either a mask (high-energy tactile pattern) or minimal stimulation (low-energy smooth surface). Perceptual precision was significantly lower with the mask compared with a three-strokes control condition without an intermediate area, approaching performance in a one-stroke-control condition. In contrast, precision in the minimal stimulation condition was significantly better than in the one-stroke control condition and similar to the three-strokes control condition. In a second experiment, we varied the number of strokes across the first stimulus (one, three, five, or seven strokes) and either presented no masking or repeated masking after each stroke. Again, masking between the strokes decreased perceptual precision relative to the control conditions without masking. Precision effects of masking over different numbers of strokes were fit by a proven model on haptic serial integration (Lezkan & Drewing, Attention, Perception, & Psychophysics 80(1): 177–192, 2018b) that modeled masking by repeated disturbances in the ongoing integration. Taken together, results suggest that masking impedes the processes of haptic information preservation and integration. We conclude that a haptic sensory memory, which is comparable to iconic memory in vision, is used for integrating sequentially gathered sensory information.


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