Perceived taste and flavor of food are greatly affected by visual information, and manipulating them in projection mapping (PM) has been explored. This paper focuses on another aspect of the gustatory sense‐food texture. We investigate whether perceived food textures can be modified by the perceptually deforming effect in PM. Through a user study, we found that the perceived softness of a pudding could be significantly increased by amplifying the apparent movement of the pudding. Interestingly, other gustatory perceptions unrelated to food textures were not affected. We believe that this result expands the potential of PM-based modulation of gustatory perceptions.

In the context of expected market activities in the metaverse environment, it is necessary to consider what kind of information should be presented for products that cannot be physically inspected. Therefore, this study analyzes product reviews, which are considered a useful source of information for consumers, to investigate the elements that contribute to purchase decision-making. In this study, we focus on texture information, which is used to express the physical properties of products. Through subject experiments, we collect and analyze the impact of the presence or absence of texture information in product reviews on purchase intention.

This paper presents a novel technique for manipulating anisotropic reflection through illumination projection from multiple projectors. The method involves obtaining a reflectance matrix corresponding to the bidirectional reflectance distribution function (BRDF) from images captured using multiple cameras. This matrix is then fitted to the Ashikhmin BRDF model, and its parameters are manipulated to obtain desired images for each viewing direction. The perceptual anisotropic reflection of the target object is optically changed with illumination projection using our light-field projection system. We demonstrated the effectiveness of our technique on Japanese textiles, hairline finishing steel, and satin.