Knowing where people look and click on visual designs can provide clues about how the designs are perceived, and where the most important or relevant content lies. The most important content of a visual design can be used for effective summarization or to facilitate retrieval from a database. We present automated models that predict the relative importance of different elements in data visualizations and graphic designs. Our models are neural networks trained on human clicks and importance annotations on hundreds of designs. We collected a new dataset of crowdsourced importance, and analyzed the predictions of our models with respect to ground truth importance and human eye movements. We demonstrate how such predictions of importance can be used for automatic design retargeting and thumbnailing. User studies with hundreds of MTurk participants validate that, with limited post-processing, our importance-driven applications are on par with, or outperform, current state-of-the-art methods, including natural image saliency. We also provide a demonstration of how our importance predictions can be built into interactive design tools to offer immediate feedback during the design process.
Designers and researchers have long studied eye movements as a clue to understanding the perception of interfaces @cite_34 @cite_24 . There have also been several recent studies of eye movements and the perception of designs @cite_42 @cite_46 . However, measuring eye movements is an expensive and time-consuming process, and is rarely feasible for practical applications.
@cite_24 @cite_46 @cite_34 @cite_42
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Publisher Summary This chapter discusses the application of eye movements to user interfaces, both for analyzing interfaces (measuring usability) and as an actual control medium within a human–computer dialogue. For usability analysis, the user's eye movements are recorded during system use and later analyzed retrospectively; however, the eye movements do not affect the interface in real time. As a direct control medium, the eye movements are obtained and used in real time as an input to the user–computer dialogue. The eye movements might be the sole input, typically for disabled users or hands-busy applications, or might be used as one of several inputs, combining with mouse, keyboard, sensors, or other devices. From the perspective of mainstream eye-movement research, human–computer interaction, together with related work in the broader field of communications and media research, appears as a new and very promising area of applied work. Both basic and applied work can profit from integration within a unified field of eye­-movement research. Application of eye tracking in human–computer interaction remains a very promising approach; its technological and market barriers are finally being reduced. Information graphics, or infographics, combine elements of data visualization with design and have become an increasingly popular means for disseminating data. While several studies have suggested that aesthetics in visualization and infographics relate to desirable outcomes like engagement and memorability, it remains unknown how quickly aesthetic impressions are formed, and what it is that makes an infographic appealing. We address these questions by analyzing 1,278 participants' ratings on appeal after seeing infographics for 500ms. Our results establish that: 1) people form a reliable first impression of the appeal of an infographic based on a mere exposure effect, 2) this first impression is largely based on colorfulness and visual complexity, and 3) age, gender, and education level influence the preferred level of colorfulness and complexity. More generally, these findings suggest that outcomes such as engagement and memorability might be determined much earlier than previously thought. to the Human Visual System (HVS).- Visual Attention.- Neurological Substrate of the HVS.- Visual Psychophysics.- Taxonomy and Models of Eye Movements.- Eye Tracking Systems.- Eye Tracking Techniques.- Head-Mounted System Hardware Installation.- Head-Mounted System Software Development.- Head-Mounted System Calibration.- Table-Mounted System Hardware Installation.- Table-Mounted System Software Development.- Table-Mounted System Calibration.- Eye Movement Analysis.- Eye Tracking Methodology.- Experimental Design.- Suggested Empirical Guidelines.- Case Studies.- Eye Tracking Applications.- Diversity and Types of Eye Tracking Applications.- Neuroscience and Psychology.- Industrial Engineering and Human Factors.- Marketing Advertising.- Computer Science.- Conclusion. In this paper we move beyond memorability and investigate how visualizations are recognized and recalled. For this study we labeled a dataset of 393 visualizations and analyzed the eye movements of 33 participants as well as thousands of participant-generated text descriptions of the visualizations. This allowed us to determine what components of a visualization attract people's attention, and what information is encoded into memory. Our findings quantitatively support many conventional qualitative design guidelines, including that (1) titles and supporting text should convey the message of a visualization, (2) if used appropriately, pictograms do not interfere with understanding and can improve recognition, and (3) redundancy helps effectively communicate the message. Importantly, we show that visualizations memorable “at-a-glance” are also capable of effectively conveying the message of the visualization. Thus, a memorable visualization is often also an effective one.