Disney Enterprises, Inc.

Eth Zürich (eidgenössische Technische Hochschulze Zürich)

Kenneth Mitchell

Markus H Gross

Markus Gross

Max Grosse

Sasha Schriber

Bochang Moon

Maria Cabral

Alfredo M Ayala, Jr

Barbara Solenthaler

David Sinclair

Jeremy Oliveira Stolarz

Steven McDonagh

Matthew W Mccrory

Moritz N Bächer

Caio Jose Dos Santos Brito

Sohyeon Jeong

Joel D Castellon

Techniques for animatronic design are provided. A plurality of simulated meshes is generated using a physics simulation model, where the plurality of simulated meshes corresponds to a plurality of actuator configurations for an animatronic mechanical design. A machine learning model is trained based on the plurality of simulated meshes and the plurality of actuator configurations. A plurality of predicted meshes is generated for the animatronic mechanical design, using the machine learning model, based on a second plurality of actuator configurations. Virtual animation of the animatronic mechanical design is facilitated based on the plurality of predicted meshes.

Machine learning for animatronic development and optimization

Systems and methods are disclosed for modifying labeled target content for a capture device. A computer-implemented method may use a computer system that includes non-transient electronic storage, a graphical user interface, and one or more physical computer processors. The computer-implemented method may include: obtaining labeled target content, the labeled target content including one or more facial features that have been labeled; modifying the labeled target content to match dynamically captured content from a first capture device to generate modified target content; and storing the modified target content. The dynamically captured content may include the one or more facial features.

Systems and methods for modifying labeled content

A method of rendering content items on a display via an electronic device involves mapping linked content items to a three-dimensional object defined by layout data. The layout data is then transmitted to an electronic device for display.

Visualisation and navigation of transmedia content data

Embodiments can provide adaptive image filtering. Under this approach, image quality can be enhanced by adjusting an approximation function to better adapt image signals in different parts of an image. Certain parts of the image may be enhanced using a certain approximation function while some other parts of the image may be enhanced using a different approximation function. In certain embodiments, the approximation function selected for a part of the image can be a polynomial function having a specific order. The specific polynomial order can be applied directly to obtain an estimated image value of the part of the image. In certain embodiments, the estimation of the reconstruction error can include iteratively estimating a bias term of the reconstruction error and a variance term of the reconstruction error.

Adaptive polynomial rendering

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Burbank, CA, United States of America

Kenneth Mitchell