Vision is much more skillful than we imagine. Visual perception results from "interpretations" of the retinal images. The visual system has many important features including adaptation to visual environments, integration of various visual clues to estimate 3D information, etc. Understanding these functions could bring about remarkable progress to media technology. Although we are almost always subjected to a barrage of different source of visual information, our visual system does not process all the information. Rather, by so-called visual attention, the visual system selectively processes some extent of the input image. To explore the fundamental functions of the vision, we are doing psychophysical experiment, and constructing mathematical models of human vision.
In many cases, we can identify the material of objects that we saw only for a moment. Not only the identification of the material, we can also discriminate the condition of objects, and furthermore evaluate the qualities of objects. To reveal whether the perception of surface qualities or conditions of objects is due to the visual information obtained from eye, we conduct experiments using not only images, such as CG and photographs, but also using real objects. For example, we focus to pearl on our study. To analyze the visual information that experts used to appraise quality of pearl, we investigated the relationship between environment and result of appraisal of the pearl. Furthermore, we are trying to reveal whether there is learning effect of visual skills by comparing experts and non-experts.
We live with a lot of things which compose several materials on their surface (e.g. metal, glass and wood). It is basic task for human visualsystem to classify their materials. However, this mechanism of the human visual system is not clear. We focus on classifying the changing of highlight and albedo on material surface, and study the separating mechanism of them by two approaches, which are machine learning and psychophysical experiment. In machine learning, we try to classify two groups of images (e.g. glossy or not) by statistical analysis method. By this process, the images are correlated with mechanism of the human visual system. In psychophysical experiment, we examine what kind of images relate to surface material by judging and rating tasks with observers. And then, their results are applied to machine learing as the feedback, and we develop new model. To continue this cycle, we are trying to improve the machine learing model, and to reveal the mechanism of the human visual system.
Experts in visual art, painters, sculptors or designers, undoubtedly have special talents for depicting objects. It should be a reasonable guess that their visual inspection is also superior. However, it is still unclear what is the difference between them and novices in vision; what do experts acquire during thousands of hours training? The aim of this study is to investigate how their visual abilities to perceive the surface quality were different from those of novices.
The quality of pearl is graded by well-trained experts’visual inspection. They have been thought to evaluate pearls according to their glossiness, interference color, shape, etc. However, the characteristics of their evaluations are not fully understood. Using pearl grading experiments, we investigate the consistency of novice (i.e., without knowledge of pearl grading) and expert participants’pearl grading skill and then compare the novices’grading with that of experts. Furthermore, we discuss the relationship between grading, interference color, and glossiness. We found that novices’grading was significantly less concordant with experts average grading than was experts’grading; more than half of novices graded pearls the opposite of how experts graded those same pearls. However, while experts graded pearls more consistently than novices did, novices’consistency was relatively high. We also found differences between the groups in regression analyses. These indicate that novices can also make use of pearls’glossiness and interference color, but that their usage is simpler than that of the experts. These results suggest that experts and novices share some values about pearls but that the evaluation method is elaborated for experts.
The glare illusion is one of the opticall illusions, which induces brightness enhancement and self-luminosity of the center white region. In upper figure, the center regionss of three glare illusions have same luminance respectively. However, we see brighter one glare stimulus which has gradient than others and feel glowing like a self-luminosity object. In our lab, we modify the luminance and color of these glare illusions and investigate their mechanism in our brains. By resent studies, we find that color gradation more enhances the glare illusion, in particular, red and blue hues are effective.
The materials such as a mirror and glass have similar characteristics that the surrounding environment is reflected or transmitted depending on their shape. However, we usually can distinguish between their materials easily. We have been investigating about the visual cue for perceptual discrimination between mirror and glass objects. The result showed that the information caused by a motion and the color polarity are essential to estimate surface material.
Here we would have an easy experiment. “Among indigenous people living deep in the mountains of Canada, one of these figure is called Bouba and another one is called Kiki. Please guess which is which” Most of us will associate Bouba with rounded shape, and Kiki with pointed shape regardless of our mother language. This phenomenon is called “Bouba-kiki effect”. This is one of a sound symbolic effect. In Shitsukan, previous studies showed that there exists sound symbolic effect also in Shitsukan. We are investigating these relationship between sound and Shitsukan using Japanese onomatopoeias.
In our surroundings, there are many things which we can recognize easier using the "color", such as traffic signals, route map. Color that we see every day is the sense produced by a human visual system - the cerebral system. According to previous studies, the mechanism of color perception (color vision) has been revealed. These results of color vision research have been applied to RGB display, data compression technologies and so on. The elucidation of characteristics of human color vision can contribute to development of new visual display system that corresponds to the characteristics of human color vision.
We can find many items colored by fluorescent color easily. Fluorescence is the emission of light by materials that has absorbed a light or other electromagnetic radiation, which is a form of luminescene. However, the perception of fluorescence occurs not only to a fluorescent material but also a non-fluorescent material, for example pictures on a monitor, fashion magazine and so on. The mechanism of perception of fluorescence has not been explained because only few researchers have studied about this. In this laboratory, we are researching about mechanism of perception of fluorescence. Therefor we are trying to determine the way to measure how fluorescent and to reveal the perceptiual meaning of fluorescence.
According to studies on human chromatic mechanisms, representation of color information in human visual system depends on level of color-information processing. For example, at an initial stage, color information is represented by three different classes of cones, and then they are linearly combined and transformed to the next cone-opponent representation. Meanwhile, details of functions of post cone-opponent level, referred to as “higher-order chromatic mechanisms”, are still unclear. In our laboratory, we employ the Classification Image (CI) technique that enables us to investigate information related to observers’ response from random chromatic noise, which leads to understand the characteristics of higher-order chromatic mechanisms and construct its mathematical model.
Sato T., Nagai T., Nakauchi S., Reverse correlation analysis of chromatic contrast perception based on chromatic mechanism models, Optical Review, Vol.21, No.5, pp.526-540 (2014/10)
Light reflected from the surface of an object can be separated as diffuse reflection component that depicts colors and patterns, and specular reflection component that depicts glare. Recent studies have suggested that we can perceive surface qualities (e.g. glossiness, transparency) by the relationship between these reflection components. However, it is still unclear whether diffuse and specular components are distinguished and separately processed in the visual system. In our laboratory, we employ the chromatic adaptation on object images with rich surface qualities to show the evidence of existence of the distinct mechanisms for diffuse and specular components.