Projektbeschreibung
Autonome Kameras behalten das Ziel im Auge
Die im letzten Jahrzehnt zu beobachtenden, geradezu verblüffenden Fortschritte in der Qualität der Smartphonekameras bezeugen die Revolution in der Fotografie- und Videografie-Hardware, die zu einem großen Teil durch die sozialen Medien und das Spielen vorangetrieben wurde. Natürlich sind die Verbesserungen an der Hardware nur ein Teil der Gleichung, dank derer wir alle bessere Bilder und Videos aufnehmen können. Das EU-finanzierte Projekt SeerPredict entwickelt nun eine Softwarelösung, die den Profis dabei hilft, ihre Arbeit noch besser zu erledigen. Eine Software, die auf der Grundlage des maschinellen Lernens von Bewegungsabfolgen des menschlichen Skeletts erlernt, Skelettbewegungen bis zu zwei Sekunden im Voraus vorherzusagen, wird dafür sorgen, dass autonome Kamerasysteme ihre Ziele im Blick behalten.
Ziel
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.
Wissenschaftliches Gebiet
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencessoftwaresoftware applicationssimulation software
- natural sciencesmathematicsapplied mathematicsmathematical model
Programm/Programme
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-INNOSUP-2020-02
Finanzierungsplan
CSA-LSP - Coordination and support action Lump sumKoordinator
8092 ZURICH ETH-ZENTRUM
Schweiz
Die Organisation definierte sich zum Zeitpunkt der Unterzeichnung der Finanzhilfevereinbarung selbst als KMU (Kleine und mittlere Unternehmen).