Optical see-through Augmented Reality (OST-AR) is a developing technology with exciting applications including medicine, industry, education, and entertainment. OST-AR creates a mix of virtual and real using an optical combiner that blends images and graphics with the real-world environment. Such an overlay of visual information is simultaneously futuristic and familiar: like the sci-fi navigation and communication interfaces in movies, but also much like banal reflections in glass windows. OSTAR’s transparent displays cause background bleed-through, which distorts color and contrast, yet virtual content is usually easily understandable. Perceptual scission, or the cognitive separation of layers, is an important mechanism, influenced by transparency, depth, parallax, and more, that helps us see what is real and what is virtual. In examples from Pepper’s Ghost, veiling luminance, mixed material modes, window shopping, and today’s OST-AR systems, transparency and scission provide surprising – and ordinary – results. Ongoing psychophysical research is addressing perceived characteristics of color, material, and images in OST-AR, testing and harnessing the perceptual effects of transparency and scission. Results help both understand the visual mechanisms and improve tomorrow’s AR systems.
Ubiquitous throughout the history of photography, white borders on photo prints and vintage Polaroids remain useful as new technologies including augmented reality emerge for general use. In contemporary optical see-through augmented reality (OST-AR) displays, physical transparency limits the visibility of dark stimuli. However, recent research shows that simple image manipulations, white borders and outer glows, have a strong visual effect, making dark objects appear darker and more opaque. In this work, the practical value of known, inter-related effects including lightness induction, glare illusion, Cornsweet illusion, and simultaneous contrast are explored. The results show promising improvements to visibility and visual quality in future OST-AR interfaces.
The topic of how colour emotion and colour vision deficiencies interact with each other is barely researched, and existing studies have contradicting results. This study will investigate how these two topics interact with each other and try to prove that colour emotion is affected by colour vision deficiencies. This was done through an online colour-emotion associations questionnaire in two phases. The first phase had 60 participants, of which 15 reported having colour vision deficiencies and the second had 18 participants, of which 8 were identified to have colour vision deficiencies. Within the questionnaires, the participants selected emotions from the Geneva Emotion Wheel which they associated with 12 colour patches or 4 colour terms and then rated how strong this association is from 1 to 5. Results show indications that colour vision deficiencies lead to reduced strength of colour-emotion associations and a higher number of people who do not associate emotions with certain or all colours. Additionally, it was found that the colour vision deficiency group associates fewer emotions with each colour than the normal vision group and differences in specific colour-emotion associations were found between the two groups.
When using VRR displays, one of the recent topics of discussion among users is the flicker that appears when the refresh rate changes. Users may experience VRR flicker when transient luminance fluctuates during refresh rate changes. Unlike the flicker index used for a single static frequency, transient fluctuations on VRR displays are aperiodic and unpredictable. To explain the aperiodic property of VRR flicker, we considered the concept of human visual causality. In the aspect of interpreting the onset of the human response to luminance change in VRR waveform, we compared the results between frequency domain analysis and time domain analysis. Based on the result of testing the preservation of visual causality, we suggest a new VRR flicker index. To verify proposed VRR index, we measured VRR waveforms and test users’ flicker perception using the VESA VRR measurement tool. Additionally, in the controlled psychophysical experiment, we compared the users’ response with our proposed VRR index. As the result, the VRR index based on the time domain analysis well explained users’ experience in VRR displays.
Are we there yet? All the puzzle pieces are here: a 2” miniature portrait on ivory dated circa 1840-1842, discovered alongside a letter detailing the owner’s familial ties to Mary Todd Lincoln. This portrait’s distinctive features echo President Lincoln’s unique facial asymmetry. However, despite intensive investigation, no historical document has been found to definitively link this miniature to Lincoln. This research aims to bridge art and science to determine whether this painting represents the earliest image of Abraham Lincoln, potentially opening avenues for future collaborations in identifying historical faces from the past. A key contributor to this effort is Dr. David Stork, an Adjunct Professor at Stanford University and a leading expert in computer-based image analysis. Dr. Stork holds 64 U.S. patents and has authored over 220 peer-reviewed publications in fields such as machine learning, pattern recognition, computational optics, and the image analysis of art. His recent book, Pixels and Paintings: Foundations of Computer-Assisted Connoisseurship1, fosters a dialogue between art scholars and the computer vision community.