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Abstract
As human beings, we trust our five senses, that allow us to experience the world and communicate. Since our birth, the amount of data that every day we can acquire is impressive and such a richness reflects the complexity of humankind in arts, technology, etc. The advent of computers and the consequent progress in Data Science and Artificial Intelligence showed how large amounts of data can contain some sort of “intelligence” themselves. Machines learn and create a superimposed layer of reality.
How data generated by humans and machines are related today? To give an answer we will present three projects in the context of “Mixed Reality”, the ideal place where Reality, Virtual Reality and Augmented Reality are increasingly connected as long as data enhance the digital experiences, making them more “real”.
We will start with BRAVO, a tool that exploits the brain activity to improve the user’s learning process in real time by means of a Brain-Computer Interface that acquires EEG data.
Then we will see AUGMENTED GRAPHICS, a framework for detecting objects in the reality that can be captured easily and inserted in any digital scenario. Based on the moments invariants theory, it looks particularly designed for mobile devices, as it assumes a light concept of object detection and it works without any training set.
As third work, GLOVR, a wearable hand controller that uses inertial sensors to offer directional controls and to recognize gestures, particularly suitable for Virtual Reality applications. It features a microphone to record voice sequences that then are translated in tasks by means of a natural language web service.
For each project we will summarize the main results and we will trace some future directions of research and development.
Abstract
As human beings, we trust our five senses, that allow us to experience the world and communicate. Since our birth, the amount of data that every day we can acquire is impressive and such a richness reflects the complexity of humankind in arts, technology, etc. The advent of computers and the consequent progress in Data Science and Artificial Intelligence showed how large amounts of data can contain some sort of “intelligence” themselves. Machines learn and create a superimposed layer of reality.
How data generated by humans and machines are related today? To give an answer we will present three projects in the context of “Mixed Reality”, the ideal place where Reality, Virtual Reality and Augmented Reality are increasingly connected as long as data enhance the digital experiences, making them more “real”.
We will start with BRAVO, a tool that exploits the brain activity to improve the user’s learning process in real time by means of a Brain-Computer Interface that acquires EEG data.
Then we will see AUGMENTED GRAPHICS, a framework for detecting objects in the reality that can be captured easily and inserted in any digital scenario. Based on the moments invariants theory, it looks particularly designed for mobile devices, as it assumes a light concept of object detection and it works without any training set.
As third work, GLOVR, a wearable hand controller that uses inertial sensors to offer directional controls and to recognize gestures, particularly suitable for Virtual Reality applications. It features a microphone to record voice sequences that then are translated in tasks by means of a natural language web service.
For each project we will summarize the main results and we will trace some future directions of research and development.
Tipologia del documento
Tesi di dottorato
Autore
Marchesi, Marco
Supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Ciclo
28
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Mixed Reality, Virtual Reality, Augmented Reality, Human-Computer Interfaces,
Wearables, Natural Language Processing, Gesture Recognition, Games, Sensors, Artificial Intelligence, Machine Learning, Computer Vision
URN:NBN
DOI
10.6092/unibo/amsdottorato/7522
Data di discussione
9 Giugno 2016
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Marchesi, Marco
Supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Ciclo
28
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Mixed Reality, Virtual Reality, Augmented Reality, Human-Computer Interfaces,
Wearables, Natural Language Processing, Gesture Recognition, Games, Sensors, Artificial Intelligence, Machine Learning, Computer Vision
URN:NBN
DOI
10.6092/unibo/amsdottorato/7522
Data di discussione
9 Giugno 2016
URI
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