Descripción del proyecto
Una solución SLAM para aplicaciones en el mundo real
La localización y mapeo simultáneos (SLAM) prometen tener un efecto revolucionario en muchos campos, desde los teléfonos inteligentes hasta la realidad aumentada. Con la señal de entrada de una cámara, esta función puede identificar la posición y orientación de nuestro dispositivo para crear un mapa del entorno. El proyecto SLAM4AR, financiado con fondos europeos, desarrollará nuevos algoritmos para el movimiento de una cámara y una meticulosa reconstrucción en 3D del entorno observado. Esta tecnología también permite la introducción de objetos en el entorno 3D. Las aplicaciones para el mundo real son muchas y variadas: desde el sector de la educación (para mostrar a estudiantes de medicina la ubicación en 3D de huesos y órganos internos) a la industria (para ver la estructura interna de un motor en el campo de la mecánica del automóvil) y hasta la cultura (para que los turistas puedan navegar hacia una determinada ubicación en un museo).
Objetivo
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.
Ámbito científico
- 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
Programa(s)
Régimen de financiación
ERC-POC-LS - ERC Proof of Concept Lump Sum PilotInstitución de acogida
80333 Muenchen
Alemania