Location determination
Disclosed are systems and methods for determining a location of a customer within a store. The systems and methods may include receiving at least one image of an item located in the store. The item may be held by the customer. The systems and methods may also include creating a feature vector. The feature vector may store features of the at least one image of the item. The location of the customer may be determined using features stored in the feature vector.
1. A method for determining a location of a customer within a store, the method comprising:
receiving at least one image of an item located in the store, thy: item being held by the customer;
creating a feature vector, the feature vector storing features of the at least one image of the item; and
determining the location of the customer using features stored in the feature vector.
2. The method of claim 1 , wherein determining the location of the customer using the feature vector includes comparing the feature vector to a known feature vector.
3. The method of claim 2 , further comprising receiving the known feature vector from a remote data source.
4. The method of claim 2 , further comprising receiving the known feature vector from a local data source.
5. The method of claim 2 , further comprising eliminating at least one of a plurality of known feature vectors based on at least one feature stored in the feature vector.
6. The method of claim 2 , further comprising selecting a subset of a plurality of known feature vectors for using in determining the location of the customer.
7. The method of claim 1 , wherein the at least one images of the item includes at least two images of the item, the at least two images of the items captured at different angles relative to one another, and wherein creating the feature vector includes extracting the features from the at least two images of the item.
8. The method of claim 1 , wherein determining the location of the customer includes determining which shelf from a plurality of shelves the customer is standing proximate to using the features stored in the feature vector.
9. The method of claim 1 , wherein at least one of the features stored in the feature vector includes text printed on a package of the item.
10. The method of claim 1 , wherein at least one of the features stored in the feature vector includes a camera identifier associated with a camera that captured each of the at least one image of the item.
11. A system for determining a location of a customer within a store, the system comprising:
a processor; and
a memory storing instructions that, when executed by the processor, cause the processor to:
receive at leak one image of an item located in the store, the item being held by the customer;
create a feature vector, the feature vector storing features of the at least one image of the item; and
determine the location of the customer using features stored in the feature vector.
12. The system of claim 11 , wherein determining the location of the customer using the feature vector includes additional instructions that, when executed by the processor, cause the processor to compare the feature vector to a known feature vector.
13. The system of claim 12 , wherein the instructions, when executed by the processor, further cause the processor to receive the known feature vector from a remote data source.
14. The system of claim 12 , wherein the instructions, when executed by the processor, further cause the processor to receive the known feature vector from a local data source.
15. The system of claim 12 , wherein the instructions, when executed by the processor, further cause the processor to eliminate at least one of a plurality of known feature vectors based on at least one feature stored in the feature vector.
16. The system of claim 12 , wherein the instructions, when executed by the processor, further cause the processor to select a subset of a plurality of known feature vectors for using in determining the location of the customer.
17. The system of claim 11 , wherein the at least one images of the item includes at least two images of the item, the at least two images of the items captured at different angles relative to one another, and wherein creating the feature vector further includes additional instructions that, when executed by the processor, cause the processor to extract the features from the at least two images of the item.
18. The system of claim 11 , wherein determining the location of the customer includes additional instructions that, when executed by the processor, cause the processor to determine which shelf from a plurality of shelves the customer is standing proximate to using the features stored in the feature vector.
19. The system of claim 11 , wherein at least one of the features stored in the feature vector includes text printed on a package of the item.
20. The system of claim 11 , wherein at least one of the features stored in the feature vector includes a camera identifier associated with a camera that captured each of the at least one image of the item.