Semantic visual search engine
First Claim
Patent Images
1. A method of categorizing a plurality of items on a mobile electronic device, comprising:
- converting a plurality of items into a plurality of candidate low-level features, for each of the plurality of items, the candidate low-level features being extracted locally around salient points in the respective item; and
using a supervised learning approach to select prominent low-level features from the plurality of candidate low-level features, the prominent low-level features being associated with predefined object categories.
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Abstract
An improved method, device and computer program product for enabling a system to learn, categorize and search items such as images and video clips according to their semantic meanings. According to the present invention, prominent features can be separated from low-level features in an item using supervised learning approaches. Prominent features are used to categorize and annotate new target items. Users can then use key words and/or template items for searching through the respective database.
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Citations
26 Claims
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1. A method of categorizing a plurality of items on a mobile electronic device, comprising:
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converting a plurality of items into a plurality of candidate low-level features, for each of the plurality of items, the candidate low-level features being extracted locally around salient points in the respective item; and
using a supervised learning approach to select prominent low-level features from the plurality of candidate low-level features, the prominent low-level features being associated with predefined object categories. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer program product for categorizing a plurality of items on a mobile electronic device, comprising:
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computer code for converting a plurality of items into a plurality of candidate low-level features, for each of the plurality of items, the candidate low-level features being extracted locally around salient points in the respective item; and
computer code for using a supervised learning approach to select prominent low-level features from the plurality of candidate low-level features, the prominent low-level features being associated with predefined object categories. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21)
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22. An electronic device, comprising:
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a processor, and a memory unit operatively connected to the processor and including;
computer code for converting a plurality of items into a plurality of candidate low-level features, for each of the plurality of items, the candidate low-level features being extracted locally around salient points in the respective item; and
computer code for using a supervised learning approach to select prominent low-level features from the plurality of candidate low-level features, the prominent low-level features being associated with predefined object categories. - View Dependent Claims (23, 24, 25, 26)
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Specification