Manipulating Avatars for Enhanced Communication in Extended Reality

Hart, Jonathon D.; Piumsomboon, Thammathip; Lee, Gun; Smith, Ross; Billinghurst, Mark

doi:10.1109/icir51845.2021.00011

Cited by 13 publications

(20 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[37], [43], [45], [48], [50], [59], [62], [63], [76], [83], [84], [86] Controller 8 16 [34], [35], [39], [42], [46], [57], [70], [80] Place annotations 5 10…”

Section: Extended Reality Technologymentioning

confidence: 99%

“…[41], [86] Speech Recognition 1 2 [79] Termination of Ray 1 2 [47] Virtual Sound 1 2 [52] Heart Rate Visualization 1 2 [41] Table 4…”

Section: Extended Reality Technologymentioning

confidence: 99%

“…Improve remote collaboration 31 62% [25]- [27], [34], [37]- [40], [42], [43], [45]- [49], [51], [52], [55], [56], [60]- [63], [68], [71], [75]- [79] Evaluate UX 23 46% [26], [27], [34], [38], [43], [45], [46], [51], [53], [54], [57], [61], [65], [67]- [70], [72]- [76], [80] Present their system 16 32% [35], [37], [42], [44], [48]- [51], [56], [60], [64], [71], [74], [77], [80] Evaluate components of a system 13 26%…”

Section: Research Aims # % Sourcesmentioning

confidence: 99%

“…Method Type # Sources Experiment Within subject 14 [25], [26], [38], [40], [46], [53]- [55], [59], [67], [68], [71], [73], [78] Mixed 7 [34], [57], [61]- [63], [74], [75] Within group 9 [27], [39], [47], [52], [58], [60], [69], [70], [72] Between Groups 1 [65] Prototype User Experience Presentation 7 [35], [36], [41], [42], [49], [76], [79] Evaluation 4 [44], [50], [64], [66] User Survey 1 [37] Within group 2 [51], [77] Within Subject 4 [43], [45], [48], [56] Between Subjects 1 [80] Table 8. Summary of research methods utilized…”

Section: Research Aims # % Sourcesmentioning

confidence: 99%

“…% Sources FOV 14 28% [35], [39], [40], [48], [51], [57], [59], [60], [63], [68], [70], [78], [79] Region of Interest 14 28% [27], [34], [36], [46], [52], [54], [61], [66], [69], [74]- [76], [80] Fixations 8 16% [26], [41], [44], [50], [55], [58], [72], [73] Ray cast line 6 12% [41]- [43], [45], [65], [77] Point of focus 5 10% [25], [26], [38], [56], [62] Frustrum 4 8% [41]- [43], [45] Saccades 3 6% [37], [49], [53] Heatmap 3 6% [47], …”

mentioning

confidence: 99%

See 4 more Smart Citations

A state of the art and scoping review of embodied information behavior in shared, co-present extended reality experiences

Kathryn¹,

Arturo²,

Lydia³

et al. 2022

View full text Add to dashboard Cite

We present a state of the art and scoping review of the literature to examine embodied information behaviors, as reflected in shared gaze interactions, within co-present extended reality experiences. Recent proliferation of consumer-grade head-mounted XR displays, situated at multiple points along the Reality-Virtuality Continuum, has increased their application in social, collaborative, and analytical scenarios that utilize data and information at multiple scales. Shared gaze represents a modality for synchronous interaction in these scenarios, yet there is a lack of understanding of the implementation of shared eye gaze within co-present extended reality contexts. We use gaze behaviors as a proxy to examine embodied information behaviors. This review examines the application of eye tracking technology to facilitate interaction in multiuser XR by sharing a user's gaze, identifies salient themes within existing research since 2013 in this context, and identifies patterns within these themes relevant to embodied information behavior in XR. We review a corpus of 50 research papers that investigate the application of shared gaze and gaze tracking in XR generated using the SALSA framework and searches in multiple databases. The publications were reviewed for study characteristics, technology types, use scenarios, and task types. We construct a state-of-the field and highlight opportunities for innovation and challenges for future research directions.

show abstract

“…[37], [43], [45], [48], [50], [59], [62], [63], [76], [83], [84], [86] Controller 8 16 [34], [35], [39], [42], [46], [57], [70], [80] Place annotations 5 10…”

Section: Extended Reality Technologymentioning

confidence: 99%

“…[41], [86] Speech Recognition 1 2 [79] Termination of Ray 1 2 [47] Virtual Sound 1 2 [52] Heart Rate Visualization 1 2 [41] Table 4…”

Section: Extended Reality Technologymentioning

confidence: 99%

Section: Research Aims # % Sourcesmentioning

confidence: 99%

Section: Research Aims # % Sourcesmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

A state of the art and scoping review of embodied information behavior in shared, co-present extended reality experiences

Kathryn¹,

Arturo²,

Lydia³

et al. 2022

View full text Add to dashboard Cite

show abstract

Comparing technologies for conveying emotions through realistic avatars in virtual reality‐based metaverse experiences

Visconti

Calandra

Lamberti

2023

Computer Animation & Virtual

View full text Add to dashboard Cite

With the development of metaverse(s), industry and academia are searching for the best ways to represent users' avatars in shared virtual environments (VEs), where real‐time communication between users is required. The expressiveness of avatars is crucial for transmitting emotions that are key for social presence and user experience, and are conveyed via verbal and non‐verbal facial and body signals. In this paper, two real‐time modalities for conveying expressions in virtual reality (VR) via realistic, full‐body avatars are compared by means of a user study. The first modality uses dedicated hardware (i.e., eye and facial trackers) to allow a mapping between the user's facial expressions/eye movements and the avatar model. The second modality relies on an algorithm that, starting from an audio clip, approximates the facial motion by generating plausible lip and eye movements. The participants were requested to observe, for both the modalities, the avatar of an actor performing six scenes involving as many basic emotions. The evaluation considered mainly social presence and emotion conveyance. Results showed a clear superiority of facial tracking when compared to lip sync in conveying sadness and disgust. The same was less evident for happiness and fear. No differences were observed for anger and surprise.

show abstract

Emotional Design for In-Vehicle Infotainment Systems: An Exploratory Co-design Study

Zhou

Lan

Sun

et al. 2022

HCI in Mobility, Transport, and Automotive Systems

View full text Add to dashboard Cite

Manipulating Avatars for Enhanced Communication in Extended Reality

Cited by 13 publications

References 17 publications

A state of the art and scoping review of embodied information behavior in shared, co-present extended reality experiences

A state of the art and scoping review of embodied information behavior in shared, co-present extended reality experiences

Comparing technologies for conveying emotions through realistic avatars in virtual reality‐based metaverse experiences

Emotional Design for In-Vehicle Infotainment Systems: An Exploratory Co-design Study

Contact Info

Product

Resources

About