Zobrazeno 1 - 10
of 976
pro vyhledávání: '"Billinghurst, Mark"'
Virtual content in Augmented Reality (AR) applications can be constructed according to the designer's requirements, but real environments, are difficult to be accurate control or completely reproduce. This makes it difficult to prototype AR applicati
Externí odkaz:
http://arxiv.org/abs/2409.16037
Autor:
Cao, Jiashuo, Gao, Wujie, Pai, Yun Suen, Hoermann, Simon, Li, Chen, Baghaei, Nilufar, Billinghurst, Mark
The advent of technology-enhanced interventions has significantly transformed mental health services, offering new opportunities for delivering psychotherapy, particularly in remote settings. This paper reports on a pilot study exploring the use of V
Externí odkaz:
http://arxiv.org/abs/2409.07765
Autor:
Wen, Ruoyu, Crowe, Stephanie Elena, Gupta, Kunal, Li, Xinyue, Billinghurst, Mark, Hoermann, Simon, Allan, Dwain, Nassani, Alaeddin, Piumsomboon, Thammathip
Sensitive information detection is crucial in content moderation to maintain safe online communities. Assisting in this traditionally manual process could relieve human moderators from overwhelming and tedious tasks, allowing them to focus solely on
Externí odkaz:
http://arxiv.org/abs/2409.00940
This paper explores enhancing empathy in Large Language Models (LLMs) by integrating them with physiological data. We propose a physiological computing approach that includes developing deep learning models that use physiological data for recognizing
Externí odkaz:
http://arxiv.org/abs/2404.15351
Autor:
Yang, Ying, Dwyer, Tim, Swiecki, Zachari, Lee, Benjamin, Wybrow, Michael, Cordeil, Maxime, Wulandari, Teresa, Thomas, Bruce H., Billinghurst, Mark
We delineate the development of a mind-mapping system designed concurrently for both VR and desktop platforms. Employing an iterative methodology with groups of users, we systematically examined and improved various facets of our system, including in
Externí odkaz:
http://arxiv.org/abs/2403.13517
Autor:
Wen, Elliott, Gupta, Chitralekha, Sasikumar, Prasanth, Billinghurst, Mark, Wilmott, James, Skow, Emily, Dey, Arindam, Nanayakkara, Suranga
Researchers have used machine learning approaches to identify motion sickness in VR experience. These approaches demand an accurately-labeled, real-world, and diverse dataset for high accuracy and generalizability. As a starting point to address this
Externí odkaz:
http://arxiv.org/abs/2306.03381
The integration of emotional intelligence in machines is an important step in advancing human-computer interaction. This demands the development of reliable end-to-end emotion recognition systems. However, the scarcity of public affective datasets pr
Externí odkaz:
http://arxiv.org/abs/2306.03112
Autor:
Schlagowski, Ruben, Nazarenko, Dariia, Can, Yekta, Gupta, Kunal, Mertes, Silvan, Billinghurst, Mark, André, Elisabeth
With face-to-face music collaboration being severely limited during the recent pandemic, mixed reality technologies and their potential to provide musicians a feeling of "being there" with their musical partner can offer tremendous opportunities. In
Externí odkaz:
http://arxiv.org/abs/2301.09402
Autor:
Yang, Ying, Dwyer, Tim, Wybrow, Michael, Lee, Benjamin, Cordeil, Maxime, Billinghurst, Mark, Thomas, Bruce H.
When collaborating face-to-face, people commonly use the surfaces and spaces around them to perform sensemaking tasks, such as spatially organising documents, notes or images. However, when people collaborate remotely using desktop interfaces they no
Externí odkaz:
http://arxiv.org/abs/2210.07784
Publikováno v:
In International Journal of Human - Computer Studies October 2024 190
