User intention modeling for interactive image retrieval
First Claim
1. A method, comprising:
- receiving an image from a user via a first user interface;
inferring a search intention of the user from visual contents of the image;
selecting a search method based on the inferred search intention;
deriving one or more image features from the image as search criteria;
training a support vector machine (SVM) ranking method with the search method and the one or more derived image features;
retrieving images from a database by applying the search method and the SVM ranking method;
receiving one or more image features from the user by operation of a second user interface, the one or more image features manually selected by one or more reference strokes drawn by the user that indicate the one or more image features; and
retrieving subsequent images from the database at least in part according to the one or more image features indicated by the user.
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Abstract
A system performs user intention modeling for interactive image retrieval. In one implementation, the system uses a three stage iterative technique to retrieve images from a database without using any image tags or text descriptors. First, the user submits a query image and the system models the user'"'"'s search intention and configures a customized search to retrieve relevant images. Then, the system extends a user interface for the user to designate visual features across the retrieved images. The designated visual features refine the intention model and reconfigure the search to retrieve images that match the remodeled intention. Third, the system extends another user interface through which the user can give natural feedback about the retrieved images. The three stages can be iterated to quickly assemble a set of images that accurately fulfills the user'"'"'s search intention. They system can be used for image searching without text tags, can be used for initial text tag generation, or can be used to complement a conventional tagged-image platform.
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Citations
20 Claims
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1. A method, comprising:
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receiving an image from a user via a first user interface; inferring a search intention of the user from visual contents of the image; selecting a search method based on the inferred search intention; deriving one or more image features from the image as search criteria; training a support vector machine (SVM) ranking method with the search method and the one or more derived image features; retrieving images from a database by applying the search method and the SVM ranking method; receiving one or more image features from the user by operation of a second user interface, the one or more image features manually selected by one or more reference strokes drawn by the user that indicate the one or more image features; and retrieving subsequent images from the database at least in part according to the one or more image features indicated by the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method, comprising:
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crawling images in local files; remotely crawling images on a network; indexing the images by visual features parsed from the images, wherein the visual features are indicative of search intentions of a user modeled in an intention model; creating an images database structured by the visual features; receiving a query image from the user by operation of a first user interface; inferring a search intention of the user by extending a second user interface to receive one or more visual features manually selected by reference strokes drawn by the user on the query image; and retrieving images from the images database according to input obtained at least in part from the second user interface. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A system, comprising:
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memory; one or more processors operatively coupled to the memory; an intention-modeling engine stored in the memory and executable by the one or more processors to receive a query image from a user and iteratively refine a search intention of the user based on visual features of the query image, the visual features indicated at least in part by extending a user interface allowing the user to draw strokes on the query image to designate features and regions of interest by surrounding them with the strokes; and a retrieval engine stored in the memory and executable by the one or more processors to configure an image search based on a current state of the modeled search intention. - View Dependent Claims (19, 20)
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Specification