System and method of identifying visual objects
A system and method of identifying objects is provided. In one aspect, the system and method includes a hand-held device with a display, camera and processor. As the camera captures images and displays them on the display, the processor compares the information retrieved in connection with one image with information retrieved in connection with subsequent images. The processor uses the result of such comparison to determine the object that is likely to be of greatest interest to the user. The display simultaneously displays the images the images as they are captured, the location of the object in an image, and information retrieved for the object.
1. A computer-implemented method comprising:
detecting, by a computer, in a plurality of images, a plurality of visually distinct features including a first feature and a second feature;
obtaining, from a computer system, a respective description of each of the plurality of features, including a first description associated with the first feature and a second description associated with the second feature;
determining that the first description associated with the first feature matches the second description associated with the second feature;
determining that a first frequency count of the first description matching other descriptions in the plurality of features exceeds a frequency count of any other description in the descriptions of the plurality of features;
generating and executing a search query based at least on the first description and the first frequency count; and
selecting a highest ranking result from results returned by the search query as an optimum annotation for a first image in the plurality of images.
2. The method of claim 1 , wherein detecting a first feature, and a second feature in the image comprises:
detecting a first object and a second object in the image.
3. The method of claim 1 , wherein obtaining a first description associated with the first feature, and a second description associated with the second feature comprises:
obtaining first text that describes the first feature and second text that describes the second feature.
4. The method of claim 3 , wherein determining that the first description associated with the first feature matches the second description associated the second feature comprises:
determining that the first text describes an object and the second text describes an entity that is associated with the object.
5. The method of claim 4 , wherein determining that the first text describes an object and the second text describes an entity that is associated with the object comprises:
determining that the second text describes a logo of the entity and that the entity provides the object.
6. The method of claim 1 , wherein generating and executing a search query based at least on the first description and the frequency count comprises:
generating a search query that includes one or more search terms that correspond to the first description.
7. The method of claim 1 , further comprising:
determining an optimum object in the image using the first frequency count.
8. A system comprising:
one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
detecting, in a plurality of images, a plurality of visually distinct features including a first feature and a second feature;
obtaining a respective description of each of the plurality of features, including a first description associated with the first feature and a second description associated with the second feature;
determining that the first description associated with the first feature matches the second description associated with the second feature;
determining that a first frequency count of the first description matching other descriptions in the plurality of features exceeds a frequency count of any other description in the descriptions of the plurality of features;
generating and executing a search query based at least on the first description and the first frequency count; and
selecting a highest ranking from results returned by the search query as an optimum annotation for a first image in the plurality of images.
9. The system of claim 8 , wherein detecting a first feature and a second feature comprises:
detecting a first object and a second object in the image.
10. The system of claim 8 , wherein obtaining a first description associated with first feature and a second description associated with the second feature comprises:
obtaining first text that describes the first feature and second text that describes the second feature.
11. The system of claim 10 , wherein determining that the first description associated with the first feature matches the second description associated with the second feature comprises:
determining that the first text describes an object and the second text describes an entity that is associated with the object.
12. The system of claim 11 , wherein determining that the first text describes an object and the second text describes an entity that is associated with the object comprises:
determining that the second text describes a logo of the entity and that the entity provides the object.
13. The system of claim 8 , wherein generating and executing a search query based at least on the first description and the frequency count comprises:
generating a search query that includes one or more search terms that correspond to the first description.
14. The system of claim 8 , further comprising:
determining an optimum object in the image using the first frequency count.
15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:
detecting, in a plurality of visually distinct features including a first feature and a second, feature;
obtaining a respective description of each of the plurality of features, including a first description associated with the first feature and a second description associated with the second feature;
determining that the first description associated with the first feature matches the second description associated with the second feature;
determining that a first frequency count of the first description matching other descriptions in the plurality of features exceeds a frequency count of any other description in the descriptions of the plurality of features;
generating and executing a search query based at least on the first description and the first frequency count; and
selecting a highest ranking result from results returned by the search query as an optimum annotation for a first image in the plurality of images.
16. The medium of claim 15 , wherein detecting a first feature and a second feature comprises:
detecting a first object and identifying a second, object in the image.
17. The medium of claim 15 , wherein obtaining a first description associated with a first feature and a second description associated with the second feature comprises:
obtaining first text that describes the first feature and second text that describes the second feature.
18. The medium of claim 17 , wherein determining that the first description associated with the first feature in the image matches the second description of associated with the second feature comprises:
determining that the first text describes an object and the second text describes an entity that is associated with the object.
19. The medium of claim 18 , wherein determining that the first text describes an object and the second text describes an entity that is associated with the object comprises:
determining that the second text describes a logo of the entity and that the entity provides the object.
20. The medium of claim 15 , wherein generating and executing a search query based at least on the first description and the frequency count comprises:
generating a search query that includes one or more search terms that correspond to the first description.