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Our work investigates the influence of self-related cues in the design of virtual humans on body perception in virtual reality. In a 2×2 mixed design, 64 participants faced photorealistic virtual humans either as a motion-synchronized embodied avatar or as an autonomous moving agent, appearing subsequently with a personalized and generic texture. Our results unveil that self-related cues through embodiment and personalization yield an individual and complemented increase in participants' sense of embodiment and self-identification towards the virtual human. Different body weight modification and estimation tasks further showed an impact of both factors on participants' body weight perception. Additional analyses revealed that the participant's body mass index predicted body weight estimations in all conditions and that participants' self-esteem and body shape concerns correlated with different body weight perception results. Hence, we have demonstrated the occurrence of double standards through induced self-related cues in virtual human perception, especially through embodiment.

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Visual landmarks provide crucial information for human navigation. But what characteristics define a landmark? To be uniquely recognized, a landmark should be distinctive and salient, while providing precise and accurate positional information. It should also be permanent. For example, to find back to your car, a nearby church seems a better landmark compared with a distinct truck or bicycle, because you learned that there is a chance that these objects might move. To this end, we investigated human learning of landmark permanency for navigation while treating spatiotemporal permanency as a probabilistic property. We hypothesized that humans will be able to learn the probabilistic nature of landmark permanency and assign higher weight to more permanent landmarks. To test this hypothesis, we designed a homing task where participants had to return to a position that was surrounded by three landmarks. In the learning phase we manipulated the spatiotemporal permanency of one landmark by secretly repositioning it before participants returned home. In the test phase, we investigated the weight allocated to the nonpermanent landmark by analyzing its influence on the navigational performance during homing. We conducted four experiments: In the first two experiments we altered the statistics of permanency and accordingly found an influence on participants' behavior, nonpermanent objects were used less for finding home. In the last two experiments we investigated the role of short-term learning of novel statistics versus long-term knowledge about such statistics. No carry-over effects in Experiment 3 and very little influence of object identity with different long-term permanency characteristics in Experiment 4 revealed a dominance of short-term learning over the use of long-term a priori knowledge about object permanency. This indicates that long-term prior beliefs are quickly updated by the current permanency statistics. Taken together, consistent with a Bayesian account for navigation these results indicate that humans quickly learn and update the statistics of landmark permanency and use it in an effective way, assigning gradually more weight to the more permanent landmark and making it more important for navigation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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Motion capture of unrestrained moving animals is a major analytic tool in neuroethology and behavioral physiology. At present, several motion capture methodologies have been developed, all of which have particular limitations regarding experimental application. Whereas marker-based motion capture systems are very robust and easily adjusted to suit different setups, tracked species, or body parts, they cannot be applied in experimental situations where markers obstruct the natural behavior (e.g., when tracking delicate, elastic, and/or sensitive body structures). On the other hand, marker-less motion capture systems typically require setup- and animal-specific adjustments, for example by means of tailored image processing, decision heuristics, and/or machine learning of specific sample data. Among the latter, deep-learning approaches have become very popular because of their applicability to virtually any sample of video data. Nevertheless, concise evaluation of their training requirements has rarely been done, particularly with regard to the transfer of trained networks from one application to another. To address this issue, the present study uses insect locomotion as a showcase example for systematic evaluation of variation and augmentation of the training data. For that, we use artificially generated video sequences with known combinations of observed, real animal postures and randomized body position, orientation, and size. Moreover, we evaluate the generalization ability of networks that have been pre-trained on synthetic videos to video recordings of real walking insects, and estimate the benefit in terms of reduced requirement for manual annotation. We show that tracking performance is affected only little by scaling factors ranging from 0.5 to 1.5. As expected from convolutional networks, the translation of the animal has no effect. On the other hand, we show that sufficient variation of rotation in the training data is essential for performance, and make concise suggestions about how much variation is required. Our results on transfer from synthetic to real videos show that pre-training reduces the amount of necessary manual annotation by about 50%.

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OBJECTIVES: Visual field defects due to hemi- or quadrantanopia after stroke represent an under-recognized neurological symptom with inefficient instruments for neurorehabilitation to date. We here examined the effects of training in a virtual reality (VR) supermarket on cognitive functions, depressive symptoms, and subjective cognitive complaints in patients with hemianopia/quadrantanopia and healthy controls. METHODS: During a 14-day rehabilitation program, 20 patients and 20 healthy controls accomplished a real-life-like shopping task in a VR supermarket. A comparison between pre- and post-training standard neuropsychological measures, depressive symptoms, and subjective memory complaints allowed us to assess a putative transfer of rehabilitation effects from the training tasks to specific cognitive functions. RESULTS: The results indicate that VR training may improve performance not only in the trained task but also in specific neuropsychological functions. After the training, both patients and controls showed improved performances in visual scanning, mental rotation, visuoconstruction, and cognitive flexibility. Moreover, depressive symptoms were attenuated in both groups. In the patient group compared to the control group, the training particularly resulted in improved visual memory retrieval and reduced memory complaints. CONCLUSIONS: The results of the current study suggest that VR training can improve particularly visual-spatial skills in patients with hemianopia or quadrantanopia. Our study thus introduces an interesting novel treatment approach to improve cognitive functions relevant to daily life in stroke patients with visual field defects.

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This article investigates performance and user experience in Social Virtual Reality (SVR) targeting distributed, embodied, and immersive, face-to-face encounters. We demonstrate the close relationship between scalability, reproduction accuracy, and the resulting performance characteristics, as well as the impact of these characteristics on users co-located with larger groups of embodied virtual others. System scalability provides a variable number of co-located avatars and Al-controlled agents with a variety of different appearances, including realistic-looking virtual humans generated from photogrammetry scans. The article reports on how to meet the requirements of embodied SVR with today's technical off-the-shelf solutions and what to expect regarding features, performance, and potential limitations. Special care has been taken to achieve low latencies and sufficient frame rates necessary for reliable communication of embodied social signals. We propose a hybrid evaluation approach which coherently relates results from technical benchmarks to subjective ratings and which confirms required performance characteristics for the target scenario of larger distributed groups. A user-study reveals positive effects of an increasing number of co-located social companions on the quality of experience of virtual worlds, i.e., on presence, possibility of interaction, and co-presence. It also shows that variety in avatar/agent appearance might increase eeriness but might also stimulate an increased interest of participants about the environment.

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In this paper, we present a method for automated estimation of a human face given a skull remain. Our proposed method is based on three statistical models. A volumetric (tetrahedral) skull model encoding the variations of different skulls, a surface head model encoding the head variations, and a dense statistic of facial soft tissue thickness (FSTT). All data are automatically derived from computed tomography (CT) head scans and optical face scans. In order to obtain a proper dense FSTT statistic, we register a skull model to each skull extracted from a CT scan and determine the FSTT value for each vertex of the skull model towards the associated extracted skin surface. The FSTT values at predefined landmarks from our statistic are well in agreement with data from the literature. To recover a face from a skull remain, we first fit our skull model to the given skull. Next, we generate spheres with radius of the respective FSTT value obtained from our statistic at each vertex of the registered skull. Finally, we fit a head model to the union of all spheres. The proposed automated method enables a probabilistic face-estimation that facilitates forensic recovery even from incomplete skull remains. The FSTT statistic allows the generation of plausible head variants, which can be adjusted intuitively using principal component analysis. We validate our face recovery process using an anonymized head CT scan. The estimation generated from the given skull visually compares well with the skin surface extracted from the CT scan itself.

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OBJECTIVE: Neuropsychological patients often suffer from impairments in visual selective attention and processing capacity components. Their assessment demands a high standardization of testing conditions, which is difficult to achieve across institutions. Head-mounted displays (HMDs) provide a solution. These virtual reality devices cover the entire visual field in a shielded way and thus keep visual stimulation constant. For neuropsychological assessment with HMDs, sufficient reliability is required. We have previously demonstrated that an early developer version of an HMD can be used to reliably measure components of visual processing capacity. However, it is unclear whether this also holds for the assessment of components of visual selective attention. Moreover, it has yet to be established whether now commercially available HMDs are capable of reliable neuropsychological assessment. METHOD: We assessed the test-retest reliabilities of several components of visual selective attention and processing capacity of healthy subjects with the commercially available HTC Vive. Using an assessment procedure (combiTVA) derived from the theory of visual attention (TVA; Bundesen, 1990), we measured attentional selectivity, lateral bias, processing speed, visual working memory capacity, and the threshold of conscious perception. We compared the reliabilities of these components measured with the HTC Vive with those of a cathode ray tube (CRT) screen, the gold standard of visual presentation in the laboratory. RESULTS: Both devices provided comparable reliabilities. CONCLUSIONS: Thus, HMDs fulfill the requirement to replace standard screens. With their inherent visual standardization and portability, they offer unprecedented opportunities for neuropsychological assessment, such as computerized bedside testing and comparisons of test values across institutions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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Feedback is essential for skill acquisition as it helps identifying and correcting performance errors. Nowadays, Virtual Reality can be used as a tool to guide motor learning, and to provide innovative types of augmented feedback that exceed real world opportunities. Concurrent feedback has shown to be especially beneficial for novices. Moreover, watching skilled performances helps novices to acquire a motor skill, and this effect depends on the perspective taken by the observer. To date, however, the impact of watching one's own performance together with full body superimposition of a skilled performance, either from the front or from the side, remains to be explored. Here we used an immersive, state-of-the-art, low-latency cave automatic virtual environment (CAVE), and we asked novices to perform squat movements in front of a virtual mirror. Participants were assigned to one of three concurrent visual feedback groups: participants either watched their own avatar performing full body movements or were presented with the movement of a skilled individual superimposed on their own performance during movement execution, either from a frontal or from a side view. Motor performance and cognitive representation were measured in order to track changes in movement quality as well as motor memory across time. Consistent with our hypotheses, results showed an advantage of the groups that observed their own avatar performing the squat together with the superimposed skilled performance for some of the investigated parameters, depending on perspective. Specifically, for the deepest point of the squat, participants watching the squat from the front adapted their height, while those watching from the side adapted their backward movement. In a control experiment, we ruled out the possibility that the observed improvements were due to the mere fact of performing the squat movements-irrespective of the type of visual feedback. The present findings indicate that it can be beneficial for novices to watch themselves together with a skilled performance during execution, and that improvement depends on the perspective chosen.

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This article reports the impact of the degree of personalization and individualization of users' avatars as well as the impact of the degree of immersion on typical psychophysical factors in embodied Virtual Environments. We investigated if and how virtual body ownership (including agency), presence, and emotional response are influenced depending on the specific look of users' avatars, which varied between (1) a generic hand-modeled version, (2) a generic scanned version, and (3) an individualized scanned version. The latter two were created using a state-of-the-art photogrammetry method providing a fast 3D-scan and post-process workflow. Users encountered their avatars in a virtual mirror metaphor using two VR setups that provided a varying degree of immersion, (a) a large screen surround projection (L-shape part of a CAVE) and (b) a head-mounted display (HMD). We found several significant as well as a number of notable effects. First, personalized avatars significantly increase body ownership, presence, and dominance compared to their generic counterparts, even if the latter were generated by the same photogrammetry process and hence could be valued as equal in terms of the degree of realism and graphical quality. Second, the degree of immersion significantly increases the body ownership, agency, as well as the feeling of presence. These results substantiate the value of personalized avatars resembling users' real-world appearances as well as the value of the deployed scanning process to generate avatars for VR-setups where the effect strength might be substantial, e.g., in social Virtual Reality (VR) or in medical VR-based therapies relying on embodied interfaces. Additionally, our results also strengthen the value of fully immersive setups which, today, are accessible for a variety of applications due to the widely available consumer HMDs.

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Vision unfolds as an intricate pattern of information processing over time. Studying vision and visual cognition therefore requires precise manipulations of the timing of visual stimulus presentation. Although standard computer display technologies offer great accuracy and precision of visual presentation, their temporal resolution is limited. This limitation stems from the fact that the presentation of rendered stimuli has to wait until the next refresh of the computer screen. We present a novel method for presenting visual stimuli with ultrahigh temporal resolution (<1 ms) on newly available gaming monitors. The method capitalizes on the G-Sync technology, which allows for presenting stimuli as soon as they have been rendered by the computer's graphics card, without having to wait for the next screen refresh. We provide software implementations in the three programming languages C++, Python (using PsychoPy2), and Matlab (using Psychtoolbox3). For all implementations, we confirmed the ultrahigh temporal resolution of visual presentation with external measurements by using a photodiode. Moreover, a psychophysical experiment revealed that the ultrahigh temporal resolution impacts on human visual performance. Specifically, observers' object recognition performance improved over fine-grained increases of object presentation duration in a theoretically predicted way. Taken together, the present study shows that the G-Sync-based presentation method enables researchers to investigate visual processes whose data patterns were concealed by the low temporal resolution of previous technologies. Therefore, this new presentation method may be a valuable tool for experimental psychologists and neuroscientists studying vision and its temporal characteristics.

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Cartoon characters are omnipresent in popular media. While few studies have scientifically investigated their processing, in computer graphics, efforts are made to increase realism. Yet, close approximations of reality have been suggested to evoke sometimes a feeling of eeriness, the "uncanny valley" effect. Here, we used high-density electroencephalography to investigate brain responses to professionally stylized happy, angry, and neutral character faces. We employed six face-stylization levels varying from abstract to realistic and investigated the N170, early posterior negativity (EPN), and late positive potential (LPP) event-related components. The face-specific N170 showed a u-shaped modulation, with stronger reactions towards both most abstract and most realistic compared to medium-stylized faces. For abstract faces, N170 was generated more occipitally than for real faces, implying stronger reliance on structural processing. Although emotional faces elicited highest amplitudes on both N170 and EPN, on the N170 realism and expression interacted. Finally, LPP increased linearly with face realism, reflecting activity increase in visual and parietal cortex for more realistic faces. Results reveal differential effects of face stylization on distinct face processing stages and suggest a perceptual basis to the uncanny valley hypothesis. They are discussed in relation to face perception, media design, and computer graphics.

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Neuropsychological assessment of human visual processing capabilities strongly depends on visual testing conditions including room lighting, stimuli, and viewing-distance. This limits standardization, threatens reliability, and prevents the assessment of core visual functions such as visual processing speed. Increasingly available virtual reality devices allow to address these problems. One such device is the portable, light-weight, and easy-to-use Oculus Rift. It is head-mounted and covers the entire visual field, thereby shielding and standardizing the visual stimulation. A fundamental prerequisite to use Oculus Rift for neuropsychological assessment is sufficient test-retest reliability. Here, we compare the test-retest reliabilities of Bundesen's visual processing components (visual processing speed, threshold of conscious perception, capacity of visual working memory) as measured with Oculus Rift and a standard CRT computer screen. Our results show that Oculus Rift allows to measure the processing components as reliably as the standard CRT. This means that Oculus Rift is applicable for standardized and reliable assessment and diagnosis of elementary cognitive functions in laboratory and clinical settings. Oculus Rift thus provides the opportunity to compare visual processing components between individuals and institutions and to establish statistical norm distributions.

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BACKGROUND: To increase the ecological validity of neuropsychological instruments the use of virtual reality (VR) applications can be considered as an effective tool in the field of cognitive neurorehabilitation. Despite the growing use of VR programs, only few studies have considered the application of everyday activities like shopping or travelling in VR training devices. METHODS: We developed a novel 360°-VR supermarket, which is displayed on a circular arrangement of 8 touch-screens--the "OctaVis". In this setting, healthy human adults had to memorize an auditorily presented shopping list (list A) and subsequently buy all remembered products of this list in the VR supermarket. This procedure was accomplished on three consecutive days. On day four, a new shopping list (list B) was introduced and participants had to memorize and buy only products of this list. On day five, participants had to buy all remembered items of list A again, but without new presentation of list A. Additionally, we obtained measures of participants' presence, immersion and figural-spatial memory abilities. We also tested a sample of patients with focal epilepsy with an extended version of our shopping task, which consisted of eight days of training. RESULTS: We observed a comprehensive and stable effect of learning for the number of correct products, the required time for shopping, and the length of movement trajectories in the VR supermarket in the course of the training program. Task performance was significantly correlated with participants' figural-spatial memory abilities and subjective level of immersion into the VR. CONCLUSIONS: Learning effects in our paradigm extend beyond mere verbal learning of the shopping list as the data show evidence for multi-layered learning (at least visual-spatial, strategic, and verbal) on concordant measures. Importantly, learning also correlated with measures of figural-spatial memory and the degree of immersion into the VR. We propose that cognitive training with the VR supermarket program in the OctaVis will be efficient for the assessment and training of real-life cognitive abilities in healthy subjects and patients with epilepsy. It is most likely that our findings will also apply for patients with cognitive disabilities resulting from other neurological and psychiatric syndromes.

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This survey reviews the recent advances in linear variational mesh deformation techniques. These methods were developed for editing detailed high-resolution meshes, like those produced by scanning real-world objects. The challenge of manipulating such complex surfaces is three-fold: the deformation technique has to be sufficiently fast, robust, and intuitive and easy to control to be useful for interactive applications. An intuitive, and thus predictable, deformation tool should provide physically plausible and aesthetically pleasing surface deformations, which in particular requires its geometric details to be preserved. The methods we survey generally formulate surface deformation as a global variational optimization problem that addresses the differential properties of the edited surface. Efficiency and robustness are achieved by linearizing the underlying objective functional, such that the global optimization amounts to solving a sparse linear system of equations. We review the different deformation energies and detail preservation techniques that were proposed in the recent years, together with the various techniques to rectify the linearization artifacts. Our goal is to provide the reader with a systematic classification and comparative description of the different techniques, revealing the strengths and weaknesses of each approach in common editing scenarios.

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