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Analysis of skeletal kinematics for vision-based motion capturing

Project description

Autonomous cameras keep their ‘eyes’ on the prize

The amazing advances in the quality of smartphone cameras over the last decade are testament to the revolution in photography and videography hardware spurred in large part by social media and gaming. Of course, advances in hardware are only one part of the equation that helps anyone take better pictures and videos. The EU-funded SeerPredict project is developing a software solution to help professionals do their jobs even better. Software that learns to predict skeletal motion up to two seconds in the future based on machine learning of skeletal sequences will make sure autonomous camera systems keep their targets in focus.

Objective

Seervision was founded in 2016, as a spin-off from the ETH Zürich and developed out of the Automatic Control Laboratory research group in the field of camera control. With their broad experience in the field of computer vision, machine learning and artificial intelligence, Seervision aims to develop fully autonomous camera systems based on vision-based 3D motion capturing. The goal is to predict skeletal motion for maximum of 2 seconds in future out of skeletal kinematics and 2D camera frames. Therefore a prediction model has to be developed with a machine learning algorithm to train the model with data on skeletal motion. Using a trained prediction model for skeletal motion based on 3D vision-based motion capturing, Seervision aims to control their camera systems fully autonomously. Currently, there are no such models commercially available and the level of autonomy in commercially available camera systems is much lower.

The proposed recruitment of an Innovation Associate (IA) in this project will have significant impact on the business opportunities of Seervision by bringing in the lacking expertise on skeletal motion and development of prediction models based on vision-based motion capturing. The SME IA grant will help to overcome the recruitment barriers of being a relatively unknown, small enterprise that cannot compete with the larger companies due to limited visibility, salary and recruitment budget.

Seervision wants to recruit a Computer Vision and Object Motion Engineer that understands the principles of 3D skeletal motion and is able to model and deploy machine learning algorithms within this context. The main added value of this opportunity for the IA is to pursue the transition from an academic environment focusing on basic research to a business environment focusing on developing competitive and cutting-edge products. Next to this, the IA will get the chance to influence and participate in the early stages of a young and innovative company.

Call for proposal

H2020-INNOSUP-2018-2020

See other projects for this call

Sub call

H2020-INNOSUP-2020-02

Coordinator

SEERVISION AG
Net EU contribution
€ 171 187,50
Address
WEINBERGSTRASSE 35 WEH F14
8092 ZURICH ETH-ZENTRUM
Switzerland

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Schweiz/Suisse/Svizzera Zürich Zürich
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
No data