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Titlebook: Virtual, Augmented and Mixed Reality. Applications and Case Studies; 11th International C Jessie Y.C. Chen,Gino Fragomeni Conference procee

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书目名称Virtual, Augmented and Mixed Reality. Applications and Case Studies
副标题11th International C
编辑Jessie Y.C. Chen,Gino Fragomeni
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Virtual, Augmented and Mixed Reality. Applications and Case Studies; 11th International C Jessie Y.C. Chen,Gino Fragomeni Conference procee
描述.This two-volume set LNCS 11574 and 11575 constitutes the refereed proceedings of the 11th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2019, held in July 2019 as part of HCI International 2019 in Orlando, FL, USA. . HCII 2019 received a total of 5029 submissions, of which 1275 papers and 209 posters were accepted for publication after a careful reviewing process.. The 80 papers presented in this volume were organized in topical sections named: multimodal interaction in VR, rendering, layout, visualization and navigation, avatars, embodiment and empathy in VAMR, cognitive and health issues in VAMR, VAMR and robots, VAMR in learning, training and entertainment, VAMR in aviation, industry and the military..
出版日期Conference proceedings 2019
关键词3D; artificial intelligence; augmented reality; display devices; human engineering; human robot interacti
版次1
doihttps://doi.org/10.1007/978-3-030-21565-1
isbn_softcover978-3-030-21564-4
isbn_ebook978-3-030-21565-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Scalable Representation Learning for Long-Term Augmented Reality-Based Information Delivery in Collarobot teaming. In the long-term use of AR systems for collaborative human-robot perception, one of the biggest challenges is to perform place and scene matching under long-term environmental changes, such as dramatic variations in lighting, weather and vegetation across different times of the day, m
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Augmented Reality for Human-Robot Teaming in Field Environmentsp information, sharing recognition of salient features of the environment, and establishing contextually-grounded communication. These challenges are further compounded for teams operating in field environments, which are unconstrained, uninstrumented, and unknown. While most modern studies that use
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Augmented Reality Based Actuated Monitor Manipulation from Dual Point of Viewive motion control for monitor. To solve this problem, we propose an augmented reality based interface to control monitor from dual point of view, referring to the third-person view and rear first-person view. In this system, augmented reality models used to represent monitor are superimposed on the
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Exploring Temporal Dependencies in Multimodal Referring Expressions with Mixed Realityun smoothly and naturally, a robot should be equipped with the ability to robustly disambiguate referring expressions. In this work, we propose a model that can disambiguate multimodal fetching requests using modalities such as head movements, hand gestures, and speech. We analysed the acquired data
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Mediating Human-Robot Interactions with Virtual, Augmented, and Mixed Reality HRI problems represent breakdowns in ., where poor information exchange between people and robots leads to disfluencies, incorrect mental models, poorly calibrated trust, inadequate situational awareness, etc. In this paper, I argue that the emergence of a new generation of virtual, augmented, and
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