Descrizione del progetto
Una soluzione SLAM per utilizzi nel mondo reale
Dagli smartphone alla realtà aumentata (AR, Augmented Reality), la localizzazione e mappatura simultanea (SLAM, Simultaneous Localisation And Mapping) promette una trasformazione. Essa è in grado di identificare la posizione e l’orientamento del nostro dispositivo per creare una mappa dell’ambiente attraverso un segnale di input della fotocamera. Il progetto SLAM4AR, finanziato dall’UE, svilupperà nuovi algoritmi per il movimento di una fotocamera e una ricostruzione 3D precisa dell’ambiente osservato. Questa nuova tecnologia può inoltre consentire l’inserimento di oggetti all’interno dell’ambiente 3D. Le applicazioni reali sono numerose e spaziano dall’istruzione (mostrare agli studenti di medicina la posizione di ossa e organi interni in 3D) all’industria (i meccanici di automobili possono vedere le strutture interne di un motore) e alla cultura (i turisti potranno navigare in un determinato luogo all’interno di un museo).
Obiettivo
The PoC Project SLAM4AR is focused on developing technological foundations for advanced augmented reality (AR) applications on smartphones. According to a recent study of Hampleton & Partners, the market value for AR applications is expected to break the $170 billion barrier by 2022. And a significant share of this market value will come from smartphone applications. In the PoC project SLAM4AR, we will build up on state-of-the-art algorithms for visual Simultaneous Localization and Mapping (SLAM) that we developed in the ERC CoG “3D Reloaded”. These algorithms allow one to recover the motion of a camera and a 3D reconstruction of the observed environment at unprecedented precision, robustness and large-scale capability (among existing real-time capable algorithms). We will reformulate and streamline these algorithms so that they can run on smartphones. They will leverage the smartphone’s camera and inertial sensor in order to compute in real-time both the location of the phone and a 3D map of the environment. In several AR applications, we will demonstrate that our algorithms with their superior precision and robustness serve as a key enabler for advanced AR technology. For example, we can perform object insertion (beyond Pokemon Go) in a way that dynamic objects interact more naturally and faithfully with a complex 3D environment – they accurately sit on chairs or tables, or they convincingly roll down slopes, etc. This will enable numerous AR applications such as teaching medical students about the 3D location of bones and inner organs, training novice car mechanics in the inner structures of a motor. Or navigating tourists to a desired location in a museum or a church. There is a rapidly growing market for AR applications on phones and we are convinced that our smartphone-based visual SLAM technology will serve as a key enabler.
Campo scientifico
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsmobile phones
- natural sciencescomputer and information sciencessoftwaresoftware applicationssimulation software
Programma(i)
Argomento(i)
Meccanismo di finanziamento
ERC-POC-LS - ERC Proof of Concept Lump Sum PilotIstituzione ospitante
80333 Muenchen
Germania