Descripción del proyecto
Cámaras autónomas que no pierden de vista su objetivo
Los asombrosos avances en la calidad de las cámaras de los teléfonos inteligentes logrados durante el último decenio son testimonio de la revolución en el «hardware» de fotografía y videografía impulsada, en gran medida, por las redes sociales y los juegos. No obstante, los avances en el «hardware» son solo una parte de la fórmula que ayuda a las personas a realizar mejores fotografías y vídeos. El equipo del proyecto SeerPredict, financiado con fondos europeos, está desarrollando una tecnología de «software» para ayudar a los profesionales a hacer su trabajo aún mejor. El «software» aprende a predecir el movimiento del esqueleto hasta dos segundos en el futuro gracias al aprendizaje automático a partir de secuencias esqueléticas, por lo que garantizará que los sistemas de cámaras autónomas no pierdan de vista su objetivo.
Objetivo
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.
Ámbito científico
- 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
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-INNOSUP-2020-02
Régimen de financiación
CSA-LSP - Coordination and support action Lump sumCoordinador
8092 ZURICH ETH-ZENTRUM
Suiza
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.