Pub Date : 2022-05-28DOI: 10.48550/arXiv.2205.14332
Wanshui Gan, Hongbin Xu, Yi Huang, Shifeng Chen, N. Yokoya
Neural radiance fields have made a remarkable breakthrough in the novel view synthesis task at the 3D static scene. However, for the 4D circumstance (e.g., dynamic scene), the performance of the existing method is still limited by the capacity of the neural network, typically in a multilayer perceptron network (MLP). In this paper, we utilize 3D Voxel to model the 4D neural radiance field, short as V4D, where the 3D voxel has two formats. The first one is to regularly model the 3D space and then use the sampled local 3D feature with the time index to model the density field and the texture field by a tiny MLP. The second one is in look-up tables (LUTs) format that is for the pixel-level refinement, where the pseudo-surface produced by the volume rendering is utilized as the guidance information to learn a 2D pixel-level refinement mapping. The proposed LUTs-based refinement module achieves the performance gain with little computational cost and could serve as the plug-and-play module in the novel view synthesis task. Moreover, we propose a more effective conditional positional encoding toward the 4D data that achieves performance gain with negligible computational burdens. Extensive experiments demonstrate that the proposed method achieves state-of-the-art performance at a low computational cost. The relevant code is available in https://github.com/GANWANSHUI/V4D.
{"title":"V4D: Voxel for 4D Novel View Synthesis","authors":"Wanshui Gan, Hongbin Xu, Yi Huang, Shifeng Chen, N. Yokoya","doi":"10.48550/arXiv.2205.14332","DOIUrl":"https://doi.org/10.48550/arXiv.2205.14332","url":null,"abstract":"Neural radiance fields have made a remarkable breakthrough in the novel view synthesis task at the 3D static scene. However, for the 4D circumstance (e.g., dynamic scene), the performance of the existing method is still limited by the capacity of the neural network, typically in a multilayer perceptron network (MLP). In this paper, we utilize 3D Voxel to model the 4D neural radiance field, short as V4D, where the 3D voxel has two formats. The first one is to regularly model the 3D space and then use the sampled local 3D feature with the time index to model the density field and the texture field by a tiny MLP. The second one is in look-up tables (LUTs) format that is for the pixel-level refinement, where the pseudo-surface produced by the volume rendering is utilized as the guidance information to learn a 2D pixel-level refinement mapping. The proposed LUTs-based refinement module achieves the performance gain with little computational cost and could serve as the plug-and-play module in the novel view synthesis task. Moreover, we propose a more effective conditional positional encoding toward the 4D data that achieves performance gain with negligible computational burdens. Extensive experiments demonstrate that the proposed method achieves state-of-the-art performance at a low computational cost. The relevant code is available in https://github.com/GANWANSHUI/V4D.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45880685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The natural locomotion interface is critical to the development of many VR applications. For household VR applications, there are two basic requirements: natural immersive experience and minimized space occupation. The existing locomotion strategies generally do not simultaneously satisfy these two requirements well. This paper presents a novel omnidirectional treadmill (ODT) system named Hex-Core-MK1 (HCMK1). By implementing two kinds of mirror-symmetrical spiral rollers to generate the omnidirectional velocity field, this proposed system is capable of providing real walking experiences with a full-degree of freedom in an area as small as 1.76 m2, while delivering great advantages over several existing ODT systems in terms of weight, volume, latency and dynamic performance. Compared with the sizes of Infinadeck and HCP, the two best motor-driven ODTs so far, the 8 cm height of HCMK1 is only 20% of Infinadeck and 50% of HCP. In addition, HCMK1 is a lightweight device weighing only 110 kg, which provides possibilities for further expanding VR scenarios, such as terrain simulation. The system latency of HCMK1 is only 9ms. The experiments show that HCMK1 can deliver a starting acceleration of 16.00 m/s2 and a braking acceleration of 30.00 m/s2.
{"title":"Strolling in Room-Scale VR: Hex-Core-MK1 Omnidirectional Treadmill","authors":"Ziyao Wang, Chiyi Liu, Jialiang Chen, Yao Yao, Dazheng Fang, Zhiyi Shi, Rui Yan, Yiye Wang, Kanjian Zhang, Hai Wang, Haikun Wei","doi":"10.48550/arXiv.2204.08437","DOIUrl":"https://doi.org/10.48550/arXiv.2204.08437","url":null,"abstract":"The natural locomotion interface is critical to the development of many VR applications. For household VR applications, there are two basic requirements: natural immersive experience and minimized space occupation. The existing locomotion strategies generally do not simultaneously satisfy these two requirements well. This paper presents a novel omnidirectional treadmill (ODT) system named Hex-Core-MK1 (HCMK1). By implementing two kinds of mirror-symmetrical spiral rollers to generate the omnidirectional velocity field, this proposed system is capable of providing real walking experiences with a full-degree of freedom in an area as small as 1.76 m2, while delivering great advantages over several existing ODT systems in terms of weight, volume, latency and dynamic performance. Compared with the sizes of Infinadeck and HCP, the two best motor-driven ODTs so far, the 8 cm height of HCMK1 is only 20% of Infinadeck and 50% of HCP. In addition, HCMK1 is a lightweight device weighing only 110 kg, which provides possibilities for further expanding VR scenarios, such as terrain simulation. The system latency of HCMK1 is only 9ms. The experiments show that HCMK1 can deliver a starting acceleration of 16.00 m/s2 and a braking acceleration of 30.00 m/s2.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48448721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-29DOI: 10.48550/arXiv.2203.15258
Xiaohe Ma, Ya-Qi Yu, Hongzhi Wu, Kun Zhou
We present a novel framework to efficiently acquire anisotropic reflectance in a pixel-independent fashion, using a deep gated mixture-of-experts. While existing work employs a unified network to handle all possible input, our network automatically learns to condition on the input for enhanced reconstruction. We train a gating module that takes photometric measurements as input and selects one out of a number of specialized decoders for reflectance reconstruction, essentially trading generality for quality. A common pre-trained latent-transform module is also appended to each decoder, to offset the burden of the increased number of decoders. In addition, the illumination conditions during acquisition can be jointly optimized. The effectiveness of our framework is validated on a wide variety of challenging near-planar samples with a lightstage. Compared with the state-of-the-art technique, our quality is improved with the same number of input images, and our input image number can be reduced to about 1/3 for equal-quality results. We further generalize the framework to enhance a state-of-the-art technique on non-planar reflectance scanning.
{"title":"Efficient Reflectance Capture with a Deep Gated Mixture-of-Experts","authors":"Xiaohe Ma, Ya-Qi Yu, Hongzhi Wu, Kun Zhou","doi":"10.48550/arXiv.2203.15258","DOIUrl":"https://doi.org/10.48550/arXiv.2203.15258","url":null,"abstract":"We present a novel framework to efficiently acquire anisotropic reflectance in a pixel-independent fashion, using a deep gated mixture-of-experts. While existing work employs a unified network to handle all possible input, our network automatically learns to condition on the input for enhanced reconstruction. We train a gating module that takes photometric measurements as input and selects one out of a number of specialized decoders for reflectance reconstruction, essentially trading generality for quality. A common pre-trained latent-transform module is also appended to each decoder, to offset the burden of the increased number of decoders. In addition, the illumination conditions during acquisition can be jointly optimized. The effectiveness of our framework is validated on a wide variety of challenging near-planar samples with a lightstage. Compared with the state-of-the-art technique, our quality is improved with the same number of input images, and our input image number can be reduced to about 1/3 for equal-quality results. We further generalize the framework to enhance a state-of-the-art technique on non-planar reflectance scanning.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48268495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Composite visualization is a popular design strategy that represents complex datasets by integrating multiple visualizations in a meaningful and aesthetic layout, such as juxtaposition, overlay, and nesting. With this strategy, numerous novel designs have been proposed in visualization publications to accomplish various visual analytic tasks. However, there is a lack of understanding of design patterns of composite visualization, thus failing to provide holistic design space and concrete examples for practical use. In this paper, we opted to revisit the composite visualizations in IEEE VIS publications and answered what and how visualizations of different types are composed together. To achieve this, we first constructed a corpus of composite visualizations from the publications and analyzed common practices, such as the pattern distributions and co-occurrence of visualization types. From the analysis, we obtained insights into different design patterns on the utilities and their potential pros and cons. Furthermore, we discussed usage scenarios of our taxonomy and corpus and how future research on visualization composition can be conducted on the basis of this study.
{"title":"Revisiting the Design Patterns of Composite Visualizations","authors":"Dazhen Deng, Weiwei Cui, Xiyu Meng, Mengye Xu, Yu Liao, Haidong Zhang, Yingcai Wu","doi":"10.48550/arXiv.2203.10476","DOIUrl":"https://doi.org/10.48550/arXiv.2203.10476","url":null,"abstract":"Composite visualization is a popular design strategy that represents complex datasets by integrating multiple visualizations in a meaningful and aesthetic layout, such as juxtaposition, overlay, and nesting. With this strategy, numerous novel designs have been proposed in visualization publications to accomplish various visual analytic tasks. However, there is a lack of understanding of design patterns of composite visualization, thus failing to provide holistic design space and concrete examples for practical use. In this paper, we opted to revisit the composite visualizations in IEEE VIS publications and answered what and how visualizations of different types are composed together. To achieve this, we first constructed a corpus of composite visualizations from the publications and analyzed common practices, such as the pattern distributions and co-occurrence of visualization types. From the analysis, we obtained insights into different design patterns on the utilities and their potential pros and cons. Furthermore, we discussed usage scenarios of our taxonomy and corpus and how future research on visualization composition can be conducted on the basis of this study.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43462263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-05DOI: 10.48550/arXiv.2203.02762
Wanchao Su, Hui Ye, Shu-Yu Chen, Lin Gao, Hongbo Fu
The research topic of sketch-to-portrait generation has witnessed a boost of progress with deep learning techniques. The recently proposed StyleGAN architectures achieve state-of-the-art generation ability but the original StyleGAN is not friendly for sketch-based creation due to its unconditional generation nature. To address this issue, we propose a direct conditioning strategy to better preserve the spatial information under the StyleGAN framework. Specifically, we introduce Spatially Conditioned StyleGAN (SC-StyleGAN for short), which explicitly injects spatial constraints to the original StyleGAN generation process. We explore two input modalities, sketches and semantic maps, which together allow users to express desired generation results more precisely and easily. Based on SC-StyleGAN, we present DrawingInStyles, a novel drawing interface for non-professional users to easily produce high-quality, photo-realistic face images with precise control, either from scratch or editing existing ones. Qualitative and quantitative evaluations show the superior generation ability of our method to existing and alternative solutions. The usability and expressiveness of our system are confirmed by a user study.
{"title":"DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN","authors":"Wanchao Su, Hui Ye, Shu-Yu Chen, Lin Gao, Hongbo Fu","doi":"10.48550/arXiv.2203.02762","DOIUrl":"https://doi.org/10.48550/arXiv.2203.02762","url":null,"abstract":"The research topic of sketch-to-portrait generation has witnessed a boost of progress with deep learning techniques. The recently proposed StyleGAN architectures achieve state-of-the-art generation ability but the original StyleGAN is not friendly for sketch-based creation due to its unconditional generation nature. To address this issue, we propose a direct conditioning strategy to better preserve the spatial information under the StyleGAN framework. Specifically, we introduce Spatially Conditioned StyleGAN (SC-StyleGAN for short), which explicitly injects spatial constraints to the original StyleGAN generation process. We explore two input modalities, sketches and semantic maps, which together allow users to express desired generation results more precisely and easily. Based on SC-StyleGAN, we present DrawingInStyles, a novel drawing interface for non-professional users to easily produce high-quality, photo-realistic face images with precise control, either from scratch or editing existing ones. Qualitative and quantitative evaluations show the superior generation ability of our method to existing and alternative solutions. The usability and expressiveness of our system are confirmed by a user study.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":" ","pages":"1-1"},"PeriodicalIF":5.2,"publicationDate":"2022-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47627988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Distances are commonly underperceived in virtual reality (VR), and this finding has been documented repeatedly over more than two decades of research. Yet, there is evidence that perceived distance is more accurate in modern compared to older head-mounted displays (HMDs). This meta-analysis of 131 studies describes egocentric distance perception across 20 HMDs, and also examines the relationship between perceived distance and technical HMD characteristics. Judged distance was positively associated with HMD field of view (FOV), positively associated with HMD resolution, and negatively associated with HMD weight. The effects of FOV and resolution were more pronounced among heavier HMDs. These findings suggest that future improvements in these technical characteristics may be central to resolving the problem of distance underperception in VR.
{"title":"Distance Perception in Virtual Reality: A Meta-Analysis of the Effect of Head-Mounted Display Characteristics.","authors":"Jonathan W. Kelly","doi":"10.31234/osf.io/6fps2","DOIUrl":"https://doi.org/10.31234/osf.io/6fps2","url":null,"abstract":"Distances are commonly underperceived in virtual reality (VR), and this finding has been documented repeatedly over more than two decades of research. Yet, there is evidence that perceived distance is more accurate in modern compared to older head-mounted displays (HMDs). This meta-analysis of 131 studies describes egocentric distance perception across 20 HMDs, and also examines the relationship between perceived distance and technical HMD characteristics. Judged distance was positively associated with HMD field of view (FOV), positively associated with HMD resolution, and negatively associated with HMD weight. The effects of FOV and resolution were more pronounced among heavier HMDs. These findings suggest that future improvements in these technical characteristics may be central to resolving the problem of distance underperception in VR.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49640191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.48550/arXiv.2206.12118
Qing Chen, Shixiong Cao, Jiazhe Wang, Nan Cao
—In recent years, narrative visualization has gained a lot of attention. Researchers have proposed different design spaces for various narrative visualization types and scenarios to facilitate the creation process. As users’ needs grow and automation technologies advance, more and more tools have been designed and developed. In this paper, we surveyed 122 papers and tools to study how automation can progressively engage in the visualization design and narrative process. By investigating the narrative strengths and the drawing efforts of various visualizations, we created a two-dimensional coordinate to map different visualization types. Our resulting taxonomy is organized by the seven types of narrative visualization on the +x-axis of the coordinate and the four automation levels (i.e., design space, authoring tool, AI-supported tool, and AI-generator tool) we identified from the collected work. The taxonomy aims to provide an overview of current research and development in the automation involvement of narrative visualization tools. We discuss key research problems in each category and suggest new opportunities to encourage further research in the related domain.
{"title":"How Does Automation Shape the Process of Narrative Visualization: A Survey on Tools","authors":"Qing Chen, Shixiong Cao, Jiazhe Wang, Nan Cao","doi":"10.48550/arXiv.2206.12118","DOIUrl":"https://doi.org/10.48550/arXiv.2206.12118","url":null,"abstract":"—In recent years, narrative visualization has gained a lot of attention. Researchers have proposed different design spaces for various narrative visualization types and scenarios to facilitate the creation process. As users’ needs grow and automation technologies advance, more and more tools have been designed and developed. In this paper, we surveyed 122 papers and tools to study how automation can progressively engage in the visualization design and narrative process. By investigating the narrative strengths and the drawing efforts of various visualizations, we created a two-dimensional coordinate to map different visualization types. Our resulting taxonomy is organized by the seven types of narrative visualization on the +x-axis of the coordinate and the four automation levels (i.e., design space, authoring tool, AI-supported tool, and AI-generator tool) we identified from the collected work. The taxonomy aims to provide an overview of current research and development in the automation involvement of narrative visualization tools. We discuss key research problems in each category and suggest new opportunities to encourage further research in the related domain.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":"8 1 1","pages":""},"PeriodicalIF":5.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70568051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1109/tvcg.2021.3114605
{"title":"2021 VGTC Visualization Significant New Researcher Award—Michelle Borkin, Northeastern University and Benjamin Bach, University of Edinburgh","authors":"","doi":"10.1109/tvcg.2021.3114605","DOIUrl":"https://doi.org/10.1109/tvcg.2021.3114605","url":null,"abstract":"","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":"1 1","pages":""},"PeriodicalIF":5.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62600291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.36227/techrxiv.17152460.v1
Hualong Bai, Yang Tian, Shengdong Zhao, Chi-Wing Fu, Qiong Wang, P. Heng
Kinesthetic feedback, the feeling of restriction or resistance when hands contact objects, is essential for natural freehand interaction in VR. However, inducing kinesthetic feedback using mechanical hardware can be cumbersome and hard to control in commodity VR systems. We propose the kine-appendage concept to compensate for the loss of kinesthetic feedback in virtual environments, i.e., a virtual appendage is added to the user's avatar hand; when the appendage contacts a virtual object, it exhibits transformations (rotation and deformation); when it disengages from the contact, it recovers its original appearance. A proof-of-concept kine-appendage technique, BrittleStylus, was designed to enhance isomorphic typing. Our empirical evaluations demonstrated that (i) BrittleStylus significantly reduced the uncorrected error rate of naive isomorphic typing from 6.53% to 1.92% without compromising the typing speed; (ii) BrittleStylus could induce the sense of kinesthetic feedback, the degree of which was parity with that induced by pseudo-haptic (+ visual cue) methods; and (iii) participants preferred BrittleStylus over pseudo-haptic (+ visual cue) methods because of not only good performance but also fluent hand movements.
{"title":"Kine-Appendage: Enhancing Freehand VR Interaction Through Transformations of Virtual Appendages.","authors":"Hualong Bai, Yang Tian, Shengdong Zhao, Chi-Wing Fu, Qiong Wang, P. Heng","doi":"10.36227/techrxiv.17152460.v1","DOIUrl":"https://doi.org/10.36227/techrxiv.17152460.v1","url":null,"abstract":"Kinesthetic feedback, the feeling of restriction or resistance when hands contact objects, is essential for natural freehand interaction in VR. However, inducing kinesthetic feedback using mechanical hardware can be cumbersome and hard to control in commodity VR systems. We propose the kine-appendage concept to compensate for the loss of kinesthetic feedback in virtual environments, i.e., a virtual appendage is added to the user's avatar hand; when the appendage contacts a virtual object, it exhibits transformations (rotation and deformation); when it disengages from the contact, it recovers its original appearance. A proof-of-concept kine-appendage technique, BrittleStylus, was designed to enhance isomorphic typing. Our empirical evaluations demonstrated that (i) BrittleStylus significantly reduced the uncorrected error rate of naive isomorphic typing from 6.53% to 1.92% without compromising the typing speed; (ii) BrittleStylus could induce the sense of kinesthetic feedback, the degree of which was parity with that induced by pseudo-haptic (+ visual cue) methods; and (iii) participants preferred BrittleStylus over pseudo-haptic (+ visual cue) methods because of not only good performance but also fluent hand movements.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47985780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jonathan W. Kelly, Melynda Hoover, Taylor A. Doty, A. Renner, L. Cherep, Stephen B Gilbert
The wide availability of consumer-oriented virtual reality (VR) equipment has enabled researchers to recruit existing VR owners to participate remotely using their own equipment. Yet, there are many differences between lab environments and home environments, as well as differences between participant samples recruited for lab studies and remote studies. This paper replicates a lab-based experiment on VR locomotion interfaces using a remote sample. Participants completed a triangle-completion task (travel two path legs, then point to the path origin) using their own VR equipment in a remote, unsupervised setting. Locomotion was accomplished using two versions of the teleporting interface varying in availability of rotational self-motion cues. The size of the traveled path and the size of the surrounding virtual environment were also manipulated. Results from remote participants largely mirrored lab results, with overall better performance when rotational self-motion cues were available. Some differences also occurred, including a tendency for remote participants to rely less on nearby landmarks, perhaps due to increased competence with using the teleporting interface to update self-location. This replication study provides insight for VR researchers on aspects of lab studies that may or may not replicate remotely.
{"title":"Remote research on locomotion interfaces for virtual reality: Replication of a lab-based study on teleporting interfaces","authors":"Jonathan W. Kelly, Melynda Hoover, Taylor A. Doty, A. Renner, L. Cherep, Stephen B Gilbert","doi":"10.31234/osf.io/wqcuf","DOIUrl":"https://doi.org/10.31234/osf.io/wqcuf","url":null,"abstract":"The wide availability of consumer-oriented virtual reality (VR) equipment has enabled researchers to recruit existing VR owners to participate remotely using their own equipment. Yet, there are many differences between lab environments and home environments, as well as differences between participant samples recruited for lab studies and remote studies. This paper replicates a lab-based experiment on VR locomotion interfaces using a remote sample. Participants completed a triangle-completion task (travel two path legs, then point to the path origin) using their own VR equipment in a remote, unsupervised setting. Locomotion was accomplished using two versions of the teleporting interface varying in availability of rotational self-motion cues. The size of the traveled path and the size of the surrounding virtual environment were also manipulated. Results from remote participants largely mirrored lab results, with overall better performance when rotational self-motion cues were available. Some differences also occurred, including a tendency for remote participants to rely less on nearby landmarks, perhaps due to increased competence with using the teleporting interface to update self-location. This replication study provides insight for VR researchers on aspects of lab studies that may or may not replicate remotely.","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":"13 4","pages":"2037-2046"},"PeriodicalIF":5.2,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41306297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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