PT  - JOURNAL ARTICLE
AU  - Masataka Sawayama
AU  - Yoshinori Dobashi
AU  - Makoto Okabe
AU  - Kenchi Hosokawa
AU  - Takuya Koumura
AU  - Toni Saarela
AU  - Maria Olkkonen
AU  - Shin’ya Nishida
TI  - Visual discrimination of optical material properties: a large-scale study
AID  - 10.1101/800870
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 800870
4099  - http://biorxiv.org/content/early/2019/12/02/800870.short
4100  - http://biorxiv.org/content/early/2019/12/02/800870.full
AB  - Complex visual processing involved in perceiving the object materials can be better elucidated by taking a variety of research approaches. Sharing stimulus and response data is an effective strategy to make the results of different studies directly comparable and can assist researchers with different backgrounds to jump into the field. Here, we constructed a database containing a variety of material images annotated with visual discrimination performance. We created various material images by using physically-based computer graphics techniques and conducted psychophysical experiments using them in both laboratory and crowdsourcing settings. The observer’s task was to discriminate materials on six dimensions (gloss contrast, gloss sharpness, translucent vs. opaque, metal vs. plastic, metal vs. glass, and glossy vs. painted) with several task difficulties. The illumination consistency and object geometry were also varied. We used a non-verbal procedure (an oddity task) so that our database could be used in diverse cross-cultural, cross-species, clinical, and developmental studies. The results showed that discrimination performance was affected by the illumination condition and object geometry, in agreement with previous studies on gloss perception, although the pattern of effects was slightly different for some material dimensions. We also found that the ability to discriminate the spatial consistency of specular highlights in glossiness perception showed larger individual differences than in other tasks. The results obtained through crowdsourcing were strongly correlated with those obtained in the laboratory, which suggests that our database can be used even when the experimental conditions are not strictly controlled. Several projects using our dataset are underway.