Mobile application for object recognition, style transfer and image synthesis, and related systems, methods, and apparatuses
AssigneeNone recorded
InventorRobert G. Adamson, III
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AssigneeNone recorded
InventorRobert G. Adamson, III
Estimating the term…
Trained segmentation, classification, and style transformation models are used to apply style effects to image segments corresponding to objects (e.g., a portrait of a person) present in an image. When depth information is included with a source image it may be used to segment, classify, and/or apply style transformation to an image or image segments (as the case may be). One or more of the segmentation, classification, and style transformations may be performed at a computing apparatus or as a service for example, in the cloud. A model management tool implemented at a server(s) may continuously train models using supervised or unsupervised training techniques to improve the quality of segmentation, classification and style transformation as well as add new capabilities. Updated models may be pushed to services offering image processing. Additionally or alternatively, a mobile application can inquire about versions of models and request updated models, or in another case, the model management tool may push updates to the mobile application. Thus, the mobile application may perform on-board image processing including segmentation, classification, and style transformation.
A computing apparatus, comprising:
A portable computing apparatus, comprising:
A method implemented by a mobile application, the method comprising:
Dependencies are inferred from the claim text.
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Two-dimensional [2D] image generation: texturing; Colouring; Generation of textures or colours
Relating to the classification model, e.g. parametric or non-parametric approaches: based on distances to training or reference patterns
Segmentation; Edge detection: involving foreground-background segmentation
Two-dimensional [2D] image generation: creating or editing images; Combining images with text
About 13 years 11 months of term left · ends 10 Oct 2040 (estimated)
Disclosed embodiments relate, generally, to image processing and image editing. More specifically, some embodiments relate, generally, to deploying machine learning models for object classification and style transfer modules of a mobile application that were trained using image segments. More specifically still, some embodiments relate, generally, to deploying machine learning models for object segmentation modules of a mobile application, such models trained to segment objects from images using depth information captured by a camera of a mobile device.
Image processing is the process of using a computer to apply an algorithm (the process) to a digital image, for example to enhance or filter the digital image or to discern information about the image. Computer image editors are tools for modifying or changing a digital image in some desired manner, some of which may use image processing.
To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
FIG. 1 is a schematic diagram depicting a computing apparatus that is a non-limiting example of an operating environment configured to perform object recognition, style transfer and synthesis, in accordance with one or more embodiments.
FIG. 2A is a functional block diagram depicting an image segmentation process flow, in accordance with one or more embodiments.
In the following detailed description, reference is made to the accompanying drawings, which form a part hereof, and in which are shown, by way of illustration, specific example embodiments in which the present disclosure may be practiced. These embodiments are described in sufficient detail to enable a person of ordinary skill in the art to practice the present disclosure. Other embodiments, however, may be utilized, and structural, material, and process changes may be made without departing from the scope of the disclosure.
The illustrations presented herein are not meant to be actual views of any particular method, system, device, or structure, but are merely idealized representations that are employed to describe the embodiments of the present disclosure. The drawings presented herein are not necessarily drawn to scale. Similar structures or components in the various drawings may retain the same or similar numbering for the convenience of the reader; however, the similarity in numbering does not mean that the structures or components are necessarily identical in size, composition, configuration, or any other property.
It will be readily understood that the components of the embodiments as generally described herein and illustrated in the drawing could be arranged and designed in a wide variety of different configurations. Thus, the following description of various embodiments is not intended to limit the scope of the present disclosure, but is merely representative of various embodiments. While the various aspects of the embodiments may be presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.