In this study, we propose a video-based facial expression recognition method that utilizes the "emotion-wheel model." In research on emotions in the field of psychology, a model has been proposed in which basic emotions are arranged in a circular pattern, such as where "happiness" and "sadness" are opposites. Therefore, we utilized this knowledge as an inductive bias to improve accuracy by embedding features that are consistent with the emotion model in the process of class identification for recognizing facial expressions in videos. As a result of a performance evaluation using the CK+, MMI, and AFEW datasets, the recognition rates of the proposed method are 98.78%, 81.95%, and 55.31% for each dataset, which are 3.67%, 6.34%, and 4.9% higher than the baseline method, respectively. Furthermore, the proposed method outperforms the state-of-the-art method on MMI and AFEW.

This research investigated the psychological stressors during the COVID-19 pandemic and the effects of essential oil odor exposure. In Japan, a stay-at-home restriction order was implemented in May 2020. We sent essential oils to the homes of 30 participants. The participants received emails 5 times a day for 6 days and reported how they felt before and after the essential oil odor exposure. They also reported their circumstances and intentions. Results showed that the vitality and stability levels increased after essential oil odor exposure. Besides, four psychological stress structures were obtained. Some of the participants felt conflicted about balancing housework, childcare, and work. They were the most stressed, and their vitality and stability levels increased considerably.

In this study, we aimed to construct impression estimation models of clothing patterns based on style features and Kansei metric. We first conducted a subjective evaluation experiment and a factor analysis, and quantified visual impressions of flower patterns. Following that, we used style features using CNN as image features suitable for representing flower patterns. Then, with a Lasso regression, we reduced the dimension based on Kansei metric (impression evaluation) and modeled the relationship between visual impressions and image features. Furthermore, we implemented a pattern search system using the modeled relationship.

Realistic and interactively generated computer graphics are needed in various fields, such as for CGI-animated movie and in education. To express the realistic appearance of various materials, it is important to represent the specific optical properties for each material.

We have proposed a method for estimating the subjective age of a person; that is, a method that yields a person's age on the basis of estimations made by that person about the age of other people by observing their facial images. Thus far, experiments have shown that Japanese people tend to underestimate their subjective age. In this study, we focus on the socio-psychological effects that may influence the underestimation of subjective age. We conducted an international comparative study. In this study, experiments were performed in which American and Japanese participants viewed American facial images; in addition, the American participants also viewed Japanese facial images. Through these experiments, it was confirmed that the subjective age generally tended toward the negative direction despite differences in the nationalities and cultures of the Japanese and American participants and their facial images. Moreover, it was found that nationality and culture may have some effects on the estimation; for example, American males did not exhibit the tendency to underestimate the age, unlike Japanese male. When estimating facial images of different nationalities, the variance generally tended to be larger, although the average was similar. This study suggests that the underestimation of age occurs despite differences in Japanese and American societies and cultures; however, the tendency of underestimation of age is not related to facial images but to social and cultural factors that influence the participants.

We have defined the perception of one's own age as “subjective age”, and have so far approached using other people's facial images. In this paper, we propose a relative estimation method for subjective age by using people's speech sounds and their chronological age. A relative estimation task is performed, wherein an estimator gives rating values to other people about whether they are older or younger than the estimator. In this task, the difference in the actual age between the estimator and the rating value of the person are measured. We plot the results on a two-dimensional plane with the x-axis as the relative age and the y-axis is the estimation result. Thus, the distribution with the plotted points of upper-right direction is obtained, which is approximated by a logistic function. The zero crossing point in the approximation curve with the x-axis is defined as the shift value in the subjective age. 57 total estimators, including 28 males and 29 females from 25 to 44 years old participated in this experiment. As a result, the subjective age using speech sounds tended to be older than using facial images. The tendency was also more remarkably visible in the male groups than in the female group. However, variance was relatively higher in the male young-middle (35–44) and the female young (25–34) groups than using facial images, which indicated that the subjective age varies according to the profile of estimators, such as age and gender.

Sound and music make impressions on listeners and can change their moods. In this paper, a sound-image scale that scales the relationship between chord progressions and their images is created. First, with the MDS method, the impression-based distance between chord progressions is calculated and, at the same time, main chord progressions used for an evaluation experiment are selected. Second, with the SD method, an evaluation experiment is conducted on the main chord progressions. As an image scale, the dimensions of activity and exaltation were adopted, and the axes were handled as “cool-warm” and “active-passive.” In addition, based on factor loadings, scales are arranged on the image scale, and, based on factor points, the main chord progressions were represented on the same scale. Furthermore, the remaining chord progressions that had not been directly evaluated were mapped on the scale with the impression-based distance used. As a result, a sound-image scale concerning chord progressions was created.

We propose a relative estimation method for subjective age, imaged by ourselves, using peoples' facial images and their chronological (real) age. We experimented with a rating scale for facial images which stimulated subjects. The subject evaluated an image as looking older than themselves with a range of responses. Finding an approximation curve of this range, the zero crossing point in the approximation curve is defined as the subjective age. The experimental result shows that the subjective age tends to be found in negative direction (tendency to estimate oneself as younger than actual). Besides, there are other trends between gender, between age groups, and between the different expressions such as ordinary and smiling.

Visual simulation using computer graphics has attracted wide attention in many fields. In this paper, we propose a method of modeling and visualizing pearls to implement a pearl visual simulator. Pearls manifest a very specific optical phenomenon. To investigate this feature, we propose a physical model of blurring and pearl interference. The experimental results show that the physics-based-modeling of internal blurring in the multilayer of a pearl and the partial coherent interference model are effective for high quality pearl visualization. This paper finally describes the possibility that this simulator can be practically used in jewellery shops.

Describes the trends of the Kansei machine vision technology. This technology is expected to be a breakthrough, answering new machine vision needs such as simulating human vision, monitoring human beings and human-machine interfaces. The paper presents its application fields, technical topics and various approaches including a facial caricaturing system and a pearl-quality evaluation system.

Visual simulation using CG and VR has attracted wide attention in the machine vision field. This paper proposes a method of modeling and visualizing pearls that will be the central technique of a pearl-quality evaluation simulator. Pearls manifest a very specific optical phenomenon that is not dependent on the direction of the light source. To investigate this feature, we propose a physical model, called an illuminant model for multilayer film interference considering the multiple reflection in spherical bodies. The rendering algorithm has been configured from such representations of physical characteristics as interference, mirroring, and texture, which correspond, respectively, to the sense of depth, brightness, and grain that are the main evaluation factors obtained from psychological experiments. Further, portions of photos of real pearls and the images generated by the present method were evaluated based on a scale of psychological evaluations of pearl-like quality demonstrating, thereby, that not merely the generated images as a whole, but the respective parts of images can present such a pearl-like quality.