eXtended Reality interfaces.

Last updated on Aug 27, 2021
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XR interactions

The eXtended Reality spectrum, which includes virtual-reality and mixed-reality, allows users to experiment on diverse interactive applications with distinctive and sometimes unusual varieties of interactions.

This project aims to study and propose new interactions, always focusing on the usability and the user’s immersion in the XR scene.

The research focuses on developing innovative interfaces and interaction methods that allow the users to interact with the environment naturally and consistently.

Deep Learning Mixed Reality
Bruno A D Marques
Bruno A D Marques
Professor of Computer Science

Computer Graphics, Artificial Intelligence and Games.

Related

Publications

FPVRGame: Deep Learning for Hand Pose Recognition in Real-Time Using Low-End HMD
We used a DenseNet Convolutional Neural Network (CNN) architecture to perform the recognition in real-time, from both indoor and outdoor environments, not requiring any image segmentation process. Our research also generated a vocabulary, considering users’ preferences, seeking a set of natural and comfortable hand poses and evaluated users’ satisfaction and performance for an entertainment setup. Our recognition model achieved an accuracy of 97.89%.
Eder de Oliveira, Esteban Clua, Cristina Nader, Bruno A D Marques
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FPVRGame: Deep Learning for Hand Pose Recognition in Real-Time Using Low-End HMD
PEEK - An LSTM Recurrent Network for Motion Classification from Sparse Data
we developed a novel Recurrent Neural Network topology based on Long Short-Term Memory cells (LSTMs) that are able to classify motions sequences of different sizes.
Rafael Rego Drumond, Bruno A D Marques, Cristina Nader Vasconcelos, Esteban Clua
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PEEK - An LSTM Recurrent Network for Motion Classification from Sparse Data