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Structured knowledge modeling and extraction from images

A structured, image technology, applied in knowledge expression, computational model, neural architecture, etc., can solve problems such as impossibility

Active Publication Date: 2017-05-17
ADOBE SYST INC
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As such, conventional search techniques cannot achieve accurate search results for complex search queries such as "man feeds baby in high chair while baby holds toy"

Method used

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  • Structured knowledge modeling and extraction from images
  • Structured knowledge modeling and extraction from images
  • Structured knowledge modeling and extraction from images

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Embodiment Construction

[0025] overview

[0026] Techniques and systems are described that support knowledge extraction from images to generate descriptive summaries of images that can then be used to support image searches, automatically generate captions and metadata for images, and various other uses. A descriptive summary may describe, for example, the quality of the image as a whole as well as attributes, objects, and mutual interactions of objects within the image as described further below. Thus, while examples involving image searching are described below, these techniques are equally applicable to a variety of other examples, such as automated structured image tagging, caption generation, and the like.

[0027] First obtain training data to use machine learning to train a model to generate structured image representations. Techniques are described herein in which training data is obtained using images and associated text (e.g., captions for images that include any text describing the scen...

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Abstract

Embodiments of the invention relate to structured knowledge modeling and extraction from images. Techniques and systems are described to model and extract knowledge from images. A digital medium environment is configured to learn and use a model to compute a descriptive summarization of an input image automatically and without user intervention. Training data is used to train a model using machine learning in order to generate a structured image representation that serves as the descriptive summarization of an input image. The images and associated text are processed to extract structured semantic knowledge from the text using natural language, which is then associated with the images. The structured semantic knowledge is processed along with corresponding images to train a model using machine learning such that the model describes a relationship between text features within the structured semantic knowledge. Once the model is learned, the model is usable to process input images to generate a structured image representation of the image.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to US Provisional Patent Application No. 62 / 254,143, filed November 11, 2015, and entitled "Structured Knowledge Modeling and Extraction from Images," the disclosure of which is hereby incorporated by reference in its entirety. technical field [0003] Embodiments of the present application relate to structured knowledge modeling and extraction from images. Background technique [0004] Image search involves the challenge of matching text in a search request to text associated with images (eg, tags, etc.). For example, a creative professional can capture an image and associate a label with text for locating the image. On the other hand, a user attempting to locate an image in an image search enters one or more keywords. Thus, this requires the creative professional and the user to come to a consensus on how to use text to describe the image so that the user can locate the image and t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06N3/04G06N3/08G06N7/00
CPCG06F16/5866G06N3/08G06N7/01G06N3/045G06N5/022G06F40/30G06N20/00
Inventor S·D·科恩W·W-T·常B·L·普赖斯M·H·M·A·埃尔霍塞尼
Owner ADOBE SYST INC
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