Real time holography using learned error feedback
AssigneeIntel Corporation
InventorsAlexey Supikov, Qiong Huang, Ronald T. Azuma
Life of this patent
Estimating the term…
Abstract
Techniques related to generating holographic images for a holographic heads up display are discussed. Such techniques include application of a machine learning model to the target image to generate data that is used to enable the determination of a phase pattern via an iterative propagation feedback model. The iterative propagation feedback model is used to generate a feedback strength value, which is then used to generate a phase diffraction pattern for presentation at a holographic plane of the heads up display.
Claims20
A heads up display (HUD) system comprising:
- a holographic plane;
- and
- a system for generating holographic images for presentation at the holographic plane, the system comprising circuitry configured to:
- apply a machine learning model to a target holographic image to generate a feedback strength value;
- apply an iterative propagation feedback model based on the target holographic image and the feedback strength value to generate a phase diffraction pattern;
- and
- output the phase diffraction pattern for presentation at the holographic plane for generation of a corresponding holographic image.
A method for generating holographic images for presentation at a holographic plane of a heads up display, the method comprising:
- applying, via one or more processors, a machine learning model to a target holographic image to generate a feedback strength value;
- applying an iterative propagation feedback model based on the target holographic image and the feedback strength value to generate a phase diffraction pattern;
- and
- outputting the phase diffraction pattern for presentation at the holographic plane for generation of a corresponding holographic image.
A non-transitory machine readable medium comprising a plurality of instructions that, in response to being executed by a processor of a holographic heads up display system, causes the processor to perform operations comprising:
- applying a machine learning model to a target holographic image to generate a feedback strength value;
- applying an iterative propagation feedback model based on the target holographic image and the feedback strength value to generate a phase diffraction pattern for presentation at a holographic plane of the holographic heads up display system;
- and
- outputting the phase diffraction pattern for presentation at the holographic plane for generation of a corresponding holographic image.
Dependencies are inferred from the claim text.