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SLAM4AR SIGNED

Simultaneous Localization and Mapping for Augmented Reality

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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Project "SLAM4AR" data sheet

The following table provides information about the project.

Coordinator
TECHNISCHE UNIVERSITAET MUENCHEN 

Organization address
address: Arcisstrasse 21
city: MUENCHEN
postcode: 80333
website: www.tu-muenchen.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Total cost 0 €
 EC max contribution 150˙000 € (0%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2019-PoC
 Funding Scheme ERC-POC-LS
 Starting year 2019
 Duration (year-month-day) from 2019-10-01   to  2021-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TECHNISCHE UNIVERSITAET MUENCHEN DE (MUENCHEN) coordinator 150˙000.00

Map

 Project objective

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.

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The information about "SLAM4AR" are provided by the European Opendata Portal: CORDIS opendata.

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