How best to evaluate a saliency model's ability to predict where humans look in images is an open research question. The choice of evaluation metric depends on how saliency is defined and how the ground truth is represented. Metrics differ in how they rank saliency models, and this results from how false positives and false negatives are treated, whether viewing biases are accounted for, whether spatial deviations are factored in, and how the saliency maps are pre-processed. In this paper, we provide an analysis of 8 different evaluation metrics and their properties. With the help of systematic experiments and visualizations of metric computations, we add interpretability to saliency scores and more transparency to the evaluation of saliency models. Building off the differences in metric properties and behaviors, we make recommendations for metric selections under specific assumptions and for specific applications.

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What Do Different Evaluation Metrics Tell Us About Saliency Models

Moving from a set of independent virtual worlds to an integrated network of 3D virtual worlds or Metaverse rests on progress in four areas: immersive realism, ubiquity of access and identity, interoperability, and scalability. For each area, the current status and needed developments in order to achieve a functional Metaverse are described. Factors that support the formation of a viable Metaverse, such as institutional and popular interest and ongoing improvements in hardware performance, and factors that constrain the achievement of this goal, including limits in computational methods and unrealized collaboration among virtual world stakeholders and developers, are also considered.

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3D Virtual worlds and the metaverse: Current status and future possibilities

Virtual reality displays, such as head-mounted displays (HMD), afford us a superior spatial awareness by leveraging our vestibular and proprioceptive senses, as compared to traditional desktop displays. Since classical times, people have used memory palaces as a spatial mnemonic to help remember information by organizing it spatially and associating it with salient features in that environment. In this paper, we explore whether using virtual memory palaces in a head-mounted display with head-tracking (HMD condition) would allow a user to better recall information than when using a traditional desktop display with a mouse-based interaction (desktop condition). We found that virtual memory palaces in HMD condition provide a superior memory recall ability compared to the desktop condition. We believe this is a first step in using virtual environments for creating more memorable experiences that enhance productivity through better recall of large amounts of information organized using the idea of virtual memory palaces.

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Virtual memory palaces: immersion aids recall

One of the current trends in distance education is the use of multi-user virtual environments (MUVE) as a training platform. MUVEs are being used for both formal and informal online learning. Second Life is a popular MUVEs being used for education today. Teaching and learning in Second Life requires a paradigm shift by educators, researchers, and learners who must adapt to a new environment of teaching and learning. Although things are done differently, many traditional learning theories can apply to Second Life. Examples of Albert Bandura’s social learning theory in Second Life are explored in this paper.

Social learning theory in Second Life

Viewpoint selection is an emerging area in computer graphics with applications in fields such as scene exploration, image-based modeling, and volume visualization. In particular, best view selection algorithms are used to obtain the minimum number of views (or images) in order to understand or model an object or scene better. In this article, we present a unified framework for viewpoint selection and mesh saliency based on the definition of an information channel between a set of viewpoints (input) and the set of polygons of an object (output). The mutual information of this channel is shown to be a powerful tool to deal with viewpoint selection, viewpoint stability, object exploration and viewpoint-based saliency. In addition, viewpoint mutual information is extended using saliency as an importance factor, showing how perceptual criteria can be incorporated to our method. Although we use a sphere of viewpoints around an object, our framework is also valid for any set of viewpoints in a closed scene. A number of experiments demonstrate the robustness of our approach and the good behavior of the proposed measures.

A unified information-theoretic framework for viewpoint selection and mesh saliency

Unlike online games, metaverses present a single seamless, persistent world where users can transparently roam around without predefined objectives. An analysis of Second Life illustrates the demands such applications place on clients, servers, and the network and suggests possible optimizations.

Second Life and the New Generation of Virtual Worlds

Recent research in visual saliency has established a computational measure of perceptual importance. In this paper we present a visual-saliency-based operator to enhance selected regions of a volume. We show how we use such an operator on a user-specified saliency field to compute an emphasis field. We further discuss how the emphasis field can be integrated into the visualization pipeline through its modifications of regional luminance and chrominance. Finally, we validate our work using an eye-tracking-based user study and show that our new saliency enhancement operator is more effective at eliciting viewer attention than the traditional Gaussian enhancement operator

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Saliency-guided Enhancement for Volume Visualization

Mesh saliency has been proposed as a computational model of perceptual importance for meshes, and it has been used in graphics for abstraction, simplification, segmentation, illumination, rendering, and illustration. Even though this technique is inspired by models of low-level human vision, it has not yet been validated with respect to human performance. Here, we present a user study that compares the previous mesh saliency approaches with human eye movements. To quantify the correlation between mesh saliency and fixation locations for 3D rendered images, we introduce the normalized chance-adjusted saliency by improving the previous chance-adjusted saliency measure. Our results show that the current computational model of mesh saliency can model human eye movements significantly better than a purely random model or a curvature-based model.

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Mesh saliency and human eye fixations

Artists, illustrators, photographers, and cinematographers have long used the principles of contrast and composition to guide visual attention. In this paper, we introduce geometry modification as a tool to persuasively direct visual attention. We build upon recent advances in mesh saliency to develop techniques to alter geometry to elicit greater visual attention. Eye-tracking-based user studies show that our approach successfully guides user attention in a statistically significant manner. Our approach operates directly on geometry and, therefore, produces view-independent results that can be used with existing view-dependent techniques of visual persuasion.

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Persuading Visual Attention through Geometry

We investigate the effects of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) and LiF interfacial layers on the efficiency of organic bulk heterojunction photodetectors fabricated with blends of regioregular poly(3-hexylthiophene-2,5-diyl) as electron donor and {6}-1-[3-(methoxycarbonyl)propyl]-{5}-1-phenyl-[5,6]-C61 as electron acceptor. At high reverse bias voltage, we find that the efficiency of these devices is limited only by the rate of creating excitons in the organic layer. Upon correction for the optical loss at the interfacial layers, the internal quantum efficiency can approach 100% in this highly disordered network of donor-acceptor molecular heterojunctions.

Youngmin Kim

Papers

Second Life and the New Generation of Virtual Worlds

Saliency-guided Enhancement for Volume Visualization

Mesh saliency and human eye fixations

Persuading Visual Attention through Geometry

Interface effects on the external quantum efficiency of organic bulk heterojunction photodetectors