Automatic method to generate product attributes based solely on product images

• US 8,582,802 B2
• Filed: 10/08/2010
• Issued: 11/12/2013
• Est. Priority Date: 10/09/2009
• Status: Active Grant

• Current Assignee: Syndigo, LLC
• Original Assignee: Edgenet, Inc. (Syndigo, LLC)
• Inventors: Clippard, Ric, Kommineni, Rajesh, Rudolph, Brian, Rudolph, Scott
• Primary Examiner(s): GORADIA, SHEFALI DINESH
• Application Number:
  US12/900,820
• Publication Number:
  US 20110085697A1
• Time in Patent Office: 1,131 Days
• Field of Search: 382/100
• US Class Current: 382/100
• CPC Class Codes: G06F 18/24323 Tree-organised classifiers
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 10/758 Involving statistics of pixels or of feature values, e.g. histogram matching
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects

Abstract

Disclosed is a method to generate data describing a product. The method includes the steps of comparing a digitized query image of the product to digitized pre-existing product images in a pre-existing product database. The pre-existing product database is organized using a taxonomy and an ontology. The pre-existing product images are linked to a corresponding node in the taxonomy and are also linked to attribute data and attribute value data in the ontology. At least one pre-existing product image is then retrieved that most closely matches the query image based on at least one matching criterion selected in whole or in part by a user. From the pre-existing product database is extracted the node in the taxonomy, the attribute data, or the attribute value data linked to the pre-existing product image retrieved earlier. In this fashion, product data relevant to the item depicted in the query image can be generated automatically from existing product data.

Claims

1. A method to generate data describing a product, the method comprising:

in a special-purpose computer or a suitably programmed general-purpose computer;

(a) comparing a digitized query image of the product to digitized pre-existing product images in a pre-existing product database, wherein the pre-existing product database comprises a taxonomy and an ontology, and the pre-existing product images are linked to a corresponding node in the taxonomy and also linked to attribute data and attribute value data in the ontology for each pre-existing product depicted in the pre-existing product images, wherein the taxonomy is organized according to attributes and attribute values relevant to appearance of the depicted pre-existing products and attributes and attribute values having no relevance to the appearance of the depicted pre-existing products;

then

(b) retrieving at least one pre-existing product image that most closely matches the query image based on at least one matching criterion selected in whole or in part by a user; and

then

(c) extracting from the pre-existing product database the node in the taxonomy, the attribute data, or the attribute value data linked to the pre-existing product image retrieved in step (b).

2. The method of claim 1, wherein step (c) comprises extracting the node in the taxonomy linked to the pre-existing product image retrieved in step (b).

3. The method of claim 2, wherein step (a) comprises comparing the query image to all of the pre-existing product images in a pre-existing product database;

and further comprising, after step (c);

(d) comparing the query image to pre-existing product images in the pre-existing product database that are indexed at the taxonomic node extracted in step (c); and

then

(e) retrieving and ranking by mathematical distance from the query image a number of pre-existing product images “

n”

from the taxonomic node extracted in step (c); and

then

(f) extracting from the “

n”

pre-existing product images retrieved and ranked in step (e) the attribute data and the attribute value data linked to the “

n”

pre-existing product images.

4. The method of claim 1, wherein step (c) comprises extracting the attribute data linked to the pre-existing product image retrieved in step (b).

5. The method of claim 1, wherein step (c) comprises extracting the attribute value data linked to the pre-existing product image retrieved in step (b).

6. The method of claim 1, wherein step (c) comprises extracting the node in the taxonomy, the attribute data, and the attribute value data linked to the pre-existing product image retrieved in step (b).

7. The method of claim 1, wherein step (b) comprises retrieving the pre-existing product image based on a matching criterion selected from the group consisting of color histogram and edge detection histogram.

8. The method of claim 1, further comprising, after step (c):

(d) associating the node in the taxonomy, the attribute data, or the attribute value data retrieved in step (b) with the query image.

9. The method of claim 8, further comprising, after step (d):

(e) saving the query image within the pre-existing product database at the associated node from step (d).

10. The method of claim 1, further comprising, after step (c):

(d) associating the node in the taxonomy retrieved in step (b) with the query image.

11. The method of claim 1, further comprising, after step (c):

(d) associating the attribute data retrieved in step (b) with the query image.

12. The method of claim 1, further comprising, after step (c):

(d) associating the attribute value data retrieved in step (b) with the query image.

13. The method of claim 1, further comprising, after step (c):

(d) associating the node in the taxonomy, the attribute data, and the attribute value data retrieved in step (b) with the query image.

14. The method of claim 13, further comprising, after step (d)

(e) saving the query image and its associated attribute data and attribute value data within the pre-existing product database at the associated node from step (d).

15. The method of claim 1, wherein the attribute data in the ontology comprise data pertaining to attributes selected from the group consisting of internal size, number of drawers, number of shelves, whether a depicted pre-existing product has an ice-maker, whether a depicted pre-existing product has a water dispenser, whether a depicted pre-existing product has a product manual, and whether a depicted pre-existing product has an extended warranty.

16. A method to generate data describing a product, the method comprising:

in a special-purpose computer or a suitably programmed general-purpose computer;

(a) comparing a digitized query image of the product to digitized pre-existing product images in a pre-existing product database, wherein the pre-existing product database comprises a taxonomy and an ontology, and the pre-existing product images are linked to a corresponding node in the taxonomy and also linked to attribute data and attribute value data in the ontology for each pre-existing product depicted in the pre-existing product images, wherein the pre-existing products depicted in the pre-existing product images are selected from the group consisting of a power tool, a hand tool, a vehicle, a padlock, a lighting fixture, a lamp, a musical instrument, a kitchen appliance, a coffee maker, a television, a mirror, furniture, a video game controller, a bathroom fixture, and a cooking tool or utensil;

then

(b) retrieving at least one pre-existing product image that most closely matches the query image based on at least one matching criterion selected in whole or in part by a user;

then

(c) extracting from the pre-existing product database the node in the taxonomy, the attribute data, and the attribute value data linked to the pre-existing product image retrieved in step (b);

then

(d) associating the node in the taxonomy, the attribute data, and the attribute value data retrieved in step (b) with the query image; and

then

(e) saving the query image and its associated attribute data and attribute value data within the pre-existing product database at the associated node from step (d).

17. The method of claim 16, wherein step (b) comprises retrieving the pre-existing product image based on a matching criterion selected from the group consisting of color histogram and edge detection histogram.

18. The method of claim 16, wherein the attribute data in the ontology comprise data pertaining to attributes selected from the group consisting of internal size, number of drawers, number of shelves, whether a depicted pre-existing product has an ice-maker, whether a depicted pre-existing product has a water dispenser, whether a depicted pre-existing product has a product manual, and whether a depicted pre-existing product has an extended warranty.

19. A method to generate data describing a product, the method comprising:

in a special-purpose computer or a suitably programmed general-purpose computer;

(a) comparing a digitized query image of the product to digitized pre-existing product images in a pre-existing product database, wherein the pre-existing product database comprises a taxonomy and an ontology, and the pre-existing product images are linked to a corresponding node in the taxonomy and also linked to attribute data and attribute value data in the ontology for each pre-existing product depicted in the pre-existing product images, wherein the taxonomy is organized according to attributes and attribute values relevant to appearance of the depicted pre-existing products and attributes and attribute values having no relevance to the appearance of the depicted pre-existing products;

then

(b) retrieving at least one pre-existing product image that most closely matches the query image based on at least one matching criterion selected in whole or in part by a user;

then

(c) extracting from the pre-existing product database the node in the taxonomy linked to the pre-existing product image retrieved in step (b);

then

(d) comparing the query image to pre-existing product images in the pre-existing product database that are indexed at the taxonomic node extracted in step (c);

then

(e) retrieving and ranking by mathematical distance from the query image a number of pre-existing product images “

n”

from the taxonomic node extracted in step (c); and

then

(f) extracting from the “

n”

pre-existing product images retrieved and ranked in step (e) the attribute data and the attribute value data linked to the “

n”

pre-existing product images.

20. The method of claim 19, further comprising, after step (f):

(g) associating the node in the taxonomy, the attribute data, and the attribute value data retrieved in step (b) with the query image; and

then

(h) saving the query image and its associated attribute data and attribute value data within the pre-existing product database at the associated node from step (g).