(b) (c) (d) (a) Figure 1: Example images rendered in real time by our method. We achieve near-accurate depth-of-field effects, including lens aberrations (e.g., spherical aberration, (a)). The efficiency of our method makes it well-suited for artistic purposes and we support complex simulations like tilt-shift photography (b). Further, our system offers an intuitive control of depth of field and we extend the physical model (c) to achieve an expressive, yet convincing result (d) (here, the background statues stay focused). Abstract We present a novel rendering system for defocus blur and lens effects. It supports physically-based rendering and outperforms previous approaches by involving a novel GPU-based tracing method. Our solution achieves more precision than competing real-time solutions and our results are mostly indistinguishable from offline rendering. Our method is also more general and can integrate advanced simulations , such as simple geometric lens models enabling various lens aberration effects. These latter is crucial for realism, but are often employed in artistic contexts, too. We show that available artistic lenses can be simulated by our method. In this spirit, our work introduces an intuitive control over depth-of-field effects. The physical basis is crucial as a starting point to enable new artistic renderings based on a generalized focal surface to emphasize particular elements in the scene while retaining a realistic look. Our real-time solution provides realistic, as well as plausible expressive results.
Figure 1: Complex lens flare generated by a Canon zoom lens. Left: reference photos. Right: renderings generated using our technique at comparable settings. Even with many unknowns in the lens design and scene composition, as well as manufacturing tolerances in the real lens, the renderings closely reproduce the "personality" of the flare. AbstractLens flare is caused by light passing through a photographic lens system in an unintended way. Often considered a degrading artifact, it has become a crucial component for realistic imagery and an artistic means that can even lead to an increased perceived brightness. So far, only costly offline processes allowed for convincing simulations of the complex light interactions. In this paper, we present a novel method to interactively compute physically-plausible flare renderings for photographic lenses. The underlying model covers many components that are important for realism, such as imperfections, chromatic and geometric lens aberrations, and antireflective lens coatings. Various acceleration strategies allow for a performance/quality tradeoff, making our technique applicable both in real-time applications and in high-quality production rendering. We further outline artistic extensions to our system.
Visualization techniques often use color to present categorical differences to a user. When selecting a color palette, the perceptual qualities of color need careful consideration. Large coherent groups visually suppress smaller groups and are often visually dominant in images. This paper introduces the concept of class visibility used to quantitatively measure the utility of a color palette to present coherent categorical structure to the user. We present a color optimization algorithm based on our class visibility metric to make categorical differences clearly visible to the user. We performed two user experiments on user preference and visual search to validate our visibility measure over a range of color palettes. The results indicate that visibility is a robust measure, and our color optimization can increase the effectiveness of categorical data visualizations.
Background Social anxiety disorder (SAD) is characterized by excessive fear of negative evaluation and humiliation in social interactions and situations. Virtual reality (VR) treatment is a promising intervention option for SAD. Objective The purpose of this study was to create a participatory and interactive VR intervention for SAD. Treatment progress, including the severity of symptoms and the cognitive and emotional aspects of SAD, was analyzed to evaluate the effectiveness of the intervention. Methods In total, 32 individuals with SAD and 34 healthy control participants were enrolled in the study through advertisements for online bulletin boards at universities. A VR intervention was designed consisting of three stages (introduction, core, and finishing) and three difficulty levels (easy, medium, and hard) that could be selected by the participants. The core stage was the exposure intervention in which participants engaged in social situations. The effectiveness of treatment was assessed through Beck Anxiety inventory (BAI), State‐Trait Anxiety Inventory (STAI), Internalized Shame Scale (ISS), Post-Event Rumination Scale (PERS), Social Phobia Scale (SPS), Social Interaction Anxiety Scale (SIAS), Brief-Fear of Negative Evaluation Scale (BFNE), and Liebowitz Social Anxiety Scale (LSAS). Results In the SAD group, scores on the BAI (F=4.616, P=.009), STAI-Trait (F=4.670, P=.004), ISS (F=6.924, P=.001), PERS-negative (F=1.008, P<.001), SPS (F=8.456, P<.001), BFNE (F=6.117, P=.004), KSAD (F=13.259, P<.001), and LSAS (F=4.103, P=.009) significantly improved over the treatment process. Compared with the healthy control group before treatment, the SAD group showed significantly higher scores on all scales (P<.001), and these significant differences persisted even after treatment (P<.001). In the comparison between the VR treatment responder and nonresponder subgroups, there was no significant difference across the course of the VR session. Conclusions These findings indicated that a participatory and interactive VR intervention had a significant effect on alleviation of the clinical symptoms of SAD, confirming the usefulness of VR for the treatment of SAD. VR treatment is expected to be one of various beneficial therapeutic approaches in the future. Trial Registration Clinical Research Information Service (CRIS) KCT0003854; https://cris.nih.go.kr/cris/search/search_result_st01.jsp?seq=13508
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