Holistic Processing Affects Surface Texture Perception: Approach from Japanese Sound Symbolic Words
분야
사회과학 > 심리학
저자
( Jinhwan Kwon ) , ( Tatsuki Kagitani ) , ( Maki Sakamoto )
발행기관
서울대학교 인지과학연구소
간행물정보
Journal of Cognitive Science 2017년, 제18권 제3호, 321~340쪽(총20쪽)
파일형식
1r300316.pdf [무료 PDF 뷰어 다운로드]
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    영문초록
    The human visual system is able to perceive not only the macrostructure (form and shape) of a surface, but also its microstructure (texture). Some evidence suggests that microstructural characteristics are processed independently of macrostructural features. However, the human visual system can interpret a variety of information about the physical world, enabling the recognition and semantic categorization of complex visual scenes at a glance. This remarkable perceptual ability relies heavily on holistic processing, which is achieved by estimating the global statistical summary of an image. On the other hand, texture is an important source of information for distinguishing between artificial and naturally occurring surfaces in images. In addition, it is reported that Japanese sound symbolic words are useful to express fine differences in texture and synesthetic characteristics. However, there is no evidence comparing the characteristics of surface texture perception between whole- and part-based images using sound symbolic words. The objective of the present study was to examine whether sound symbolic words for describing the surface texture perception differs between whole-based images related to the holistic processing and part-based images. In Experiment 1, we examined the effect of wholebased images in surface texture perception using sound symbolic words. In Experiment 2, we examined the effect of part-based images in surface texture perception using sound symbolic words. The results revealed that the sensory and symbolic descriptors differed in texture perceptions between whole-based and part-based image processing. These findings suggest that sound symbolic words can describe differences in surface texture between whole-based and part-based images at a fine resolution.
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