1 research outputs found
Using CNNs For Users Segmentation In Video See-Through Augmented Virtuality
In this paper, we present preliminary results on the use of deep learning
techniques to integrate the users self-body and other participants into a
head-mounted video see-through augmented virtuality scenario. It has been
previously shown that seeing users bodies in such simulations may improve the
feeling of both self and social presence in the virtual environment, as well as
user performance. We propose to use a convolutional neural network for real
time semantic segmentation of users bodies in the stereoscopic RGB video
streams acquired from the perspective of the user. We describe design issues as
well as implementation details of the system and demonstrate the feasibility of
using such neural networks for merging users bodies in an augmented virtuality
simulation.Comment: 6 pages, 6 figures. Published in the 2nd International Conference on
Artificial Intelligence & Virtual Reality (IEEE AIVR 2019