Machine learning based image processing techniques
AssigneeOutward, Inc.
InventorsClarence Chui, Manu Parmar
Life of this patent
Estimating the term…
Abstract
A machine learning based image processing architecture and associated applications are disclosed herein. In some embodiments, a machine learning framework is trained to learn low level image attributes such as object/scene types, geometries, placements, materials and textures, camera characteristics, lighting characteristics, contrast, noise statistics, etc. Thereafter, the machine learning framework may be employed to detect such attributes in other images and process the images at the attribute level.
Claims25
A method, comprising:
- identifying a set of one or more attributes shared by a set of input images using a machine learning framework, wherein the set of input images is constrained to a prescribed scene type and wherein the machine learning framework is at least in part trained on a set of training images comprising the prescribed scene type;
- and
- generating a set of one or more output images of the prescribed scene type having at least the same shared set of one or more attributes as the set of input images.
A system, comprising:
- a processor configured to:
- identify a set of one or more attributes shared by a set of input images using a machine learning framework, wherein the set of input images is constrained to a prescribed scene type and wherein the machine learning framework is at least in part trained on a set of training images comprising the prescribed scene type;
- and
- generate a set of one or more output images of the prescribed scene type having at least the same shared set of one or more attributes as the set of input images;
- and
- a memory coupled to the processor and configured to provide the processor with instructions.
A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:
- identifying a set of one or more attributes shared by a set of input images using a machine learning framework, wherein the set of input images is constrained to a prescribed scene type and wherein the machine learning framework is at least in part trained on a set of training images comprising the prescribed scene type;
- and
- generating a set of one or more output images of the prescribed scene type having at least the same shared set of one or more attributes as the set of input images.
Dependencies are inferred from the claim text.