title: Temporal properties of material categorization and material rating: visual vs non-visual material features.
abstract: Humans can visually recognize material categories of objects, such as glass, stone, and plastic, easily. However, little is known about the kinds of surface quality features that contribute to such material class recognition. In this paper, we examine the relationship between perceptual surface features and material category discrimination performance for pictures of materials, focusing on temporal aspects, including reaction time and effects of stimulus duration. The stimuli were pictures of objects with an identical shape but made of different materials that could be categorized into seven classes (glass, plastic, metal, stone, wood, leather, and fabric). In a pre-experiment, observers rated the pictures on nine surface features, including visual (e.g., glossiness and transparency) and non-visual features (e.g., heaviness and warmness), on a 7-point scale. In the main experiments, observers judged whether two simultaneously presented pictures were classified as the same or different material category. Reaction times and effects of stimulus duration were measured. The results showed that visual feature ratings were correlated with material discrimination performance for short reaction times or short stimulus durations, while non-visual feature ratings were correlated only with performance for long reaction times or long stimulus durations. These results suggest that the mechanisms underlying visual and non-visual feature processing may differ in terms of processing time, although the cause is unclear. Visual surface features may mainly contribute to material recognition in daily life, while non-visual features may contribute only weakly, if at all.
authors.affiliation: Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka Tempaku, Toyohashi, Aichi 441-8580, Japan. Electronic address: tnagai@yz.yamagata-u.ac.jp.
authors.forename: Takehiro
authors.initials: T
authors.lastname: Nagai
authors.affiliation: Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka Tempaku, Toyohashi, Aichi 441-8580, Japan.
authors.forename: Toshiki
authors.initials: T
authors.lastname: Matsushima
authors.affiliation: Electronics-Inspired Interdisciplinary Research Institute, Toyohashi University of Technology, 1-1 Hibarigaoka Tempaku, Toyohashi, Aichi 441-8580, Japan.
authors.forename: Kowa
authors.initials: K
authors.lastname: Koida
authors.affiliation: Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka Tempaku, Toyohashi, Aichi 441-8580, Japan.
authors.forename: Yusuke
authors.initials: Y
authors.lastname: Tani
authors.affiliation: Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka Tempaku, Toyohashi, Aichi 441-8580, Japan.
authors.forename: Michiteru
authors.initials: M
authors.lastname: Kitazaki
authors.affiliation: Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka Tempaku, Toyohashi, Aichi 441-8580, Japan.
authors.forename: Shigeki
authors.initials: S
authors.lastname: Nakauchi
mesh_terms: D000328:Adult; D004192:Discrimination, Psychological; D005260:Female; D005556:Form Perception / Q000502:physiology*; D006801:Humans; D008297:Male; D010364:Pattern Recognition, Visual / Q000502:physiology; D010470:Perceptual Masking; D010775:Photic Stimulation / Q000379:methods; D025341:Principal Component Analysis; D011601:Psychophysics; D011930:Reaction Time; D013499:Surface Properties
keywords: Material category; Material perception; Psychophysics; Surface feature