Projection Mapping for Enhancing the Perceived Deliciousness of Food
The perceived deliciousness of a food item is highly related to its appearance. Image processing has been widely used to make food images more appealing to the public, such as when capturing and posting images on social networking sites. This paper proposes a methodology and a system to enhance the degree of subjective deliciousness perceived by a person based on the appearance of a real food item by changing its appearance in a real environment. First, an online questionnaire survey was conducted to analyze the appearance factors that make food look delicious by using various food images. Based on this knowledge, a prototype system, which projects a computer-generated image onto the food item, was constructed for enhancing its subjective degree of deliciousness based on its appearance at a pixel level. Finally, a user study was conducted in which the subjective degree of deliciousness based on food appearance was compared under various appearance modification conditions. The results show that appropriate chroma and partial-color modifications highly increase this degree of deliciousness, thus implying that the proposed system can successfully be used to improve the appearance of food to make it look more delicious.
Geometrically-Correct Projection-Based Texture Mapping onto a Deformable Object
Projection-based Augmented Reality commonly employs a rigid substrate as the projection surface and does not support scenarios where the substrate can be reshaped. This investigation presents a projection-based AR system that supports deformable substrates that can be bent, twisted or folded. We demonstrate a new invisible marker embedded into a deformable substrate and an algorithm that identifies deformation to project geometrically correct textures onto the deformable object. The geometrically correct projection-based texture mapping onto a deformable marker is conducted using the measurement of the 3D shape through the detection of the retro-reflective marker on the surface. In order to achieve accurate texture mapping, we propose a marker pattern that can be partially recognized and can be registered to an object’s surface. The outcome of this work addresses a fundamental vision recognition challenge that allows the underlying material to change shape and be recognized by the system. Our evaluation demonstrated the system achieved geometrically correct projection under extreme deformation conditions. We envisage the techniques presented are useful for domains including prototype development, design, entertainment and information based AR systems．
Relation between Displaying Features of Augmented Reality and User’s Memorization
In this investigation, we verify a hypothesis: “it has positive effects for user’s memorization ability to use features of Augmented Reality (AR)”. The basis of this hypothesis is derived from the following two features. One is a future of AR: “AR can provide information associated with specific locations in the real world”. The other is a future of human memory: “human can easily memorize information if the information
is associated with specific locations”. To verify this hypothesis, we conduct three user studies. As a result, significant differences are found between the situation in which information is associated with the location of the target object in the real world and that in which information is connected with an unrelated location.