Descrizione del progetto
Fotocamere autonome con una messa a fuoco eccezionale
Gli incredibili progressi nella qualità delle fotocamere degli smartphone nell’ultimo decennio testimoniano la rivoluzione verificatasi nell’hardware della fotografia e della videoripresa, stimolata in gran parte dai social media e dai videogiochi. Naturalmente, i progressi a livello di hardware sono solo una parte dell’equazione grazie alla quale chiunque può scattare foto e girare video migliori. Il progetto SeerPredict, finanziato dall’UE, sta sviluppando una soluzione software per aiutare i professionisti a fare ancora meglio il loro lavoro. Un software che impara a prevedere il movimento scheletrico fino a due secondi nel futuro, basato sull’apprendimento automatico delle sequenze scheletriche, farà in modo che i sistemi di telecamere autonome mantengano i loro obiettivi a fuoco.
Obiettivo
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.
Campo scientifico
- 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
Programma(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-INNOSUP-2020-02
Meccanismo di finanziamento
CSA-LSP - Coordination and support action Lump sumCoordinatore
8092 ZURICH ETH-ZENTRUM
Svizzera
L’organizzazione si è definita una PMI (piccola e media impresa) al momento della firma dell’accordo di sovvenzione.