Abstract
The importance of interpersonal and group communication has been studied and recognized for thousands of years. With recent technological advances, humans have enabled remote interaction through shared virtual spaces; however, research is still needed to develop methods for expressing many important non-verbal communication cues. Our work explores the methods for enhancing the communication spectrum in collaborative virtual environments. Our primary contribution is a machine learning framework that maps human facial data to avatars in the virtual world. We developed a synthetic training process to create labeled data to alleviate the burden of manual annotation. Additionally, we describe a collaborative virtual environment that can utilize both verbal and non-verbal cues for improved user communication and interaction. Finally, we present results demonstrating the success of our method in a sample collaborative scenario.
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Kim, E., Moritz, C. (2016). Enhancing the Communication Spectrum in Collaborative Virtual Environments. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10072. Springer, Cham. https://doi.org/10.1007/978-3-319-50835-1_61
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DOI: https://doi.org/10.1007/978-3-319-50835-1_61
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