Microsoft. has filed a patent for a data processing system that generates images based on textual queries by predicting color palettes associated with the subject matter. The system uses machine learning models trained on abstract imagery to create images with specific content and style limitations. GlobalData’s report on Microsoft gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Microsoft, AI for workflow management was a key innovation area identified from patents. Microsoft's grant share as of January 2024 was 56%. Grant share is based on the ratio of number of grants to total number of patents.
Procedurally generating images based on textual input
The patent application (Publication Number: US20240037810A1) describes a data processing system that generates abstract images based on textual inputs. The system includes a processor and a machine-readable medium storing executable instructions. These instructions enable the processor to receive a textual input containing a query for an image, analyze the input to predict a color palette associated with the query, and procedurally generate the image using the predicted color palette. The system uses procedural generation algorithms to limit the content types and style included in the generated image, ensuring it remains abstract and excludes representations of people, animals, or objects from the physical world.
Furthermore, the system incorporates machine learning models to enhance the image generation process. It can submit the textual input to a search engine to obtain a sample image for color palette extraction or provide the input to machine learning models trained to predict color palettes based on query complexity, mood, and sentiment. The system also allows user-specified constraints to define the properties of the generated abstract images, ensuring they meet specific requirements. Additionally, the system includes mechanisms to detect and prevent the generation of abstract images containing objectionable or inappropriate content, enhancing the overall quality and appropriateness of the generated images. Overall, the data processing system described in the patent application offers a sophisticated and efficient approach to generating abstract images based on textual inputs, leveraging procedural generation algorithms and machine learning models to enhance the image creation process.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
