A BFigure 1: Exemplary result of the visualization system that enables the seamless transition between abstract graphics (A) and a photorealistic version (B) view-dependently. The sequence below shows single frames of this transition. AbstractVirtual 3D city models play an important role in the communication of complex geospatial information in a growing number of applications, such as urban planning, navigation, tourist information, and disaster management. In general, homogeneous graphic styles are used for visualization. For instance, photorealism is suitable for detailed presentations, and non-photorealism or abstract stylization is used to facilitate guidance of a viewer's gaze to prioritized information. However, to adapt visualization to different contexts and contents and to support saliencyguided visualization based on user interaction or dynamically changing thematic information, a combination of different graphic styles is necessary. Design and implementation of such combined graphic styles pose a number of challenges, specifically from the perspective of real-time 3D visualization. In this paper, the authors present a concept and an implementation of a system that enables different presentation styles, their seamless integration within a single view, and parametrized transitions between them, which are defined according to tasks, camera view, and image resolution. The paper outlines potential usage scenarios and application fields together with a performance evaluation of the implementation.

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Original photo of a lasagna dish.Output of HueShift2. Output of FlowAbs [Kyprianidis and Döllner 2008].Figure 1: Two techniques studied in this article, each using a different strategy for making surgery images easier to look at. ABSTRACTWe present the first empirical study on using color manipulation and stylization to make surgery images more palatable. While aversion to such images is natural, it limits many people's ability to satisfy their curiosity, educate themselves, and make informed decisions. We selected a diverse set of image processing techniques, and tested them both on surgeons and lay people. While many artistic methods were found unusable by surgeons, edge-preserving image smoothing gave good results both in terms of preserving information (as judged by surgeons) and reducing repulsiveness (as judged by lay people). Color manipulation turned out to be not as effective. CCS CONCEPTS• Computing methodologies → Non-photorealistic rendering; Image processing; • Human-centered computing → Empirical studies in HCI ; * Lonni Besançon is also with Linköping University, Sweden.Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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We present the first empirical study on using colour manipulation and stylization to make surgery images/videos more palatable. While aversion to such material is natural, it limits many people's ability to satisfy their curiosity, educate themselves and make informed decisions. We selected a diverse set of image processing techniques to test them both on surgeons and lay people. While colour manipulation techniques and many artistic methods were found unusable by surgeons, edge‐preserving image smoothing yielded good results both for preserving information (as judged by surgeons) and reducing repulsiveness (as judged by lay people). We then conducted a second set of interview with surgeons to assess whether these methods could also be used on videos and derive good default parameters for information preservation. We provide extensive supplemental material at https://osf.io/4pfes/.

Intensity Intensity 0 1 0 1 Pixels Pixels ground rooftop original output original post-processing proposed proposed method post-process filtering texture lod post-process filtering proposed method Figure 1: Exemplary results of a coherence-enhancing filtering (top) and flow-based difference-of-Gaussians filtering (FDoG, bottom) for a textured 3D scene, rendered in real-time using our system. The closeups and scanline plots (FDoG) illustrate the high accuracy for texture gradients when using our methods instead of conventional filtering in a post-process stage on the rendered color image (top right). AbstractTexture mapping is a key technology in computer graphics for visual design of rendered 3D scenes. An effective information transfer of surface properties, encoded by textures, however, depends significantly on how important information is highlighted and cognitively processed by the user in an application context. Edge-preserving image filtering is a promising approach to address this concern while preserving global salient structures. Much research has focused on applying image filters in a post-process stage to foster an artistically stylized rendering, but these approaches are generally not able to preserve depth cues important for 3D visualization (e.g., texture gradient). To this end, filtering that processes texture data coherently with respect to linear perspective and spatial relationships is required.In this work, we present a system that enables to process textured 3D scenes with perspective coherence by arbitrary image filters. We propose decoupled deferred texturing with (1) caching strategies to interactively perform image filtering prior to texture mapping, and (2) for each mipmap level separately to enable a progressive level of abstraction. We demonstrate the potentials of our methods on several applications, including illustrative visualization, focus+context visualization, geometric detail removal, and depth of field. Our system supports frame-to-frame coherence, order-independent transparency, multitexturing, and content-based filtering.

Input (b) Tattoo (c) Glass (d) Mystique (e) Divine (f) CartoonFigure 1: Different types of effects produced with our mobile app. It is the first that supports a large variation of image manipulation tasks within a unified framework, which is based on intrinsic image decomposition.