Computational aesthetics has become an active research field in recent years, but there have been few attempts in computational aesthetic evaluation of logos. In this article, we restrict our study on black-and-white logos, which are professionally designed for name-brand companies with similar properties, and apply perceptual models of standard design principles in computational aesthetic evaluation of logos. We define a group of metrics to evaluate some aspects in design principles such as balance, contrast, and harmony of logos. We also collect human ratings of balance, contrast, harmony, and aesthetics of 60 logos from 60 volunteers. Statistical linear regression models are trained on this database using a supervised machine-learning method. Experimental results show that our model-evaluated balance, contrast, and harmony have highly significant correlation of over 0.87 with human evaluations on the same dimensions. Finally, we regress human-evaluated aesthetics scores on model-evaluated balance, contrast, and harmony. The resulted regression model of aesthetics can predict human judgments on perceived aesthetics with a high correlation of 0.85. Our work provides a machine-learning-based reference framework for quantitative aesthetic evaluation of graphic design patterns and also the research of exploring the relationship between aesthetic perceptions of human and computational evaluation of design principles extracted from graphic designs.

Feature integration theory, the classic visual attention model, provides a theoretical foundation for optimizing visual communication. This paper proposes a set of glyphs named RoseShape that aim at improving users' visual information search in visualization. RoseShapes integrate rich and easy-to-catch attributes for mapping data variables, enabling automatic and unconscious information processing in the pre-attentive stage. A case study illustrating the levels of education funding in the United States in 2008 validates the feasibility of this approach.

Exciting developments in eye-wearable technology and its potential industrial applications warrant a thorough understanding of its advantages and drawbacks through empirical evidence. We conducted an experiment to investigate what characteristics of eye-wearable technology impact user performance in machine maintenance, which included a representative set of car maintenance tasks involving Locate, Manipulate, and Compare actions. Participants were asked to follow instructions displayed on one of four technologies: a peripheral eye-wearable display, a central eye-wearable display, a tablet, or a paper manual. We found a significant effect of display position: the peripheral eye-wearable display resulted in longer completion time than the central display; but no effect for hands-free operation. The technology effects were also modulated by different Tasks and Action types. We discuss the human factors implications for designing more effective eye-wearable technology, including display position, issues of monocular display, and how the physical proximity of the technology affects users' reliance level.

Previous research showed that different cultures play a significant role in influencing people's perception and cognition: Eastern people attend more to the background and context, whereas western people focus more on objects. However, the culture influence on people's aesthetic perception and experience has not been systematically explored. In the first part of our study, we measured the eye movements of Chinese and western participants while they viewed Chinese traditional Ink-wash paintings, and we found that the Chinese participants had longer fixation time in the white space areas than did the western participants. In the second part of the study, we measured their eye movements while they viewed different paintings composed by the linear perspective or scattered perspective techniques, and the results suggest that the western participants are more sensitive to the perspective difference between paintings. The findings contribute to the understanding of culture influence on people's aesthetic perception of visual art and visual communication.

We developed a Chinese questionnaire for assessing the user experience of the design of interactive products. The initial Chinese UX Questionnaire was based on a widely used English questionnaire, AttracDiff, proposed and refined by Hassenzahl and his colleagues, but extended with an additional dimension and several new items received from the interviews of Chinese users. We also conducted a study of applying the initial questionnaire for accessing the user experience of interacting three different mobile phones involved with thirty-six Chinese participants. We applied both exploratory factor analysis and confirmatory factor analysis on the items with good item-total correlations. The result showed that three factors or dimensions were identified: Hedonic Quality (Stimulation), Pragmatic Quality, and Conformity, as compared to the four dimensions in the AttracDiff. This confirmed our initial hypothesis that cultures not only influence people's cognition, but also affect their experience of interacting with products. We also discuss the future steps for refining the Chinese UX Questionnaire.

In this paper, we report a study that examines the relationship between image-based computational analyses of web pages and users' aesthetic judgments about the same image material. Web pages were iteratively decomposed into quadrants of minimum entropy (quadtree decomposition) based on low-level image statistics, to permit a characterization of these pages in terms of their respective organizational symmetry, balance and equilibrium. These attributes were then evaluated for their correlation with human participants' subjective ratings of the same web pages on four aesthetic and affective dimensions. Several of these correlations were quite large and revealed interesting patterns in the relationship between low-level (i.e., pixel-level) image statistics and design-relevant dimensions.

To contribute to systems that reason about human attention, our work empirically demonstrates how a user's mental workload changes during task execution. We conducted a study where users performed interactive, hierarchical tasks while mental workload was measured through the use of pupil size. Results show that (i) different types of subtasks impose different mental workload, (ii) workload decreases at subtask boundaries, (iii) workload decreases more at boundaries higher in a task model and less at boundaries lower in the model, (iv) workload changes among subtask boundaries within the same level of a task model, and (v) effective understanding of why changes in workload occur requires that the measure be tightly coupled to a validated task model. From the results, we show how to map mental workload onto a computational Index of Opportunity that systems can use to better reason about human attention.

1. Past research in a number of fields confirms the existence of a link between cognition and eye movement control, beyond simply a pointing relationship. This being the case, it should be possible to use eye movement recording as a basis for detecting users' cognitive states in real time. Several examples of such cognitive state detectors have been reported in the literature.2. A multi-disciplinary project is described in which the goal is to provide the computer with as much real-time information about the human state (cognitive, affective and motivational state) as possible, and to base computer actions on this information. The application area in which this is being implemented is science education, learning about gears through exploration. Two studies are reported in which participants solve simple problems of pictured gear trains while their eye movements are recorded. The first study indicates that most eye movement sequences are compatible with predictions of a simple sequential cognitive model, and it is suggested that those sequences that do not fit the model may be of particular interest in the HCI context as indicating problems or alternative mental strategies. The mental rotation of gears sometimes produces sequences of short eye movements in the direction of motion; thus, such sequences may be useful as cognitive state detecto.3. The second study tested the hypothesis that participants are thinking about the object to which their eyes are directed. In this study, the display was turned off partway through the process of solving a problem, and the participants reported what they were thinking about at that time. While in most cases the participants reported cognitive activities involving the fixated object, this was not the case on a sizeable number of trials.