Self-service product return using computer vision and Artificial Intelligence

1. A method for returning an item, comprising:

performing item return operations by a computing device using at least one of machine learned information about a person who purchased the item, machine learned information about a person returning the item, and machined learned information about a condition of the item at at least one of the time of sale and at the time of return;

automatively sorting the item using a conveyer system to move the item from a counter to a respective storage area of a plurality of storage areas assigned to different product types;

performing imaging and scanning operations to determine item related information comprising at least one of a brand of the item, a product type for the item, a size of the item, a color of the item, an authentication mark made on the item, a weight of the item, and a code associated with the item; and

validating that the item is not associated with a previous return attempt based on the item related information.

2. The method according to claim 1 , further comprising performing operations by the computing device to learn features and characteristics of counterfeit items which are not consistent with features and characteristics of corresponding non-counterfeit items.

3. The method according to claim 2 , further comprising:

determining if the item is a counterfeit item based on the learned features and characteristics of counterfeit items;

allowing return of the item if it is determined that the item is not a counterfeit item; and

denying the return of the item if it is determined that the item is a counterfeit item.

4. The method according to claim 1 , further comprising verifying by the computing device that the item's return is authorized by (A) determining if a credit card number, token or code obtained from a user matches that used to purchase the item, or (B) determining if a person shown in an image captured by a camera located by a return station matches a person shown in an image captured during a purchase transaction for the item.

5. The method according to claim 1 , further comprising validating that the item being returned is a previously purchased item based on the item related information.

6. The method according to claim 1 , further comprising determining a condition of the item based on contents of an image captured while the item is being returned.

7. The method according to claim 6 , further comprising determining if the item can be resold based on the determined condition.

8. The method according to claim 6 , further comprising determining if the condition of the item is the same or different at a time of purchase and a time of return.

9. A system, comprising:

a processor;

a non-transitory computer-readable storage medium comprising programming instructions that are configured to cause the processor to implement a method for returning items in a computing device, wherein the programming instructions comprise instructions to:

perform item return operations using at least one of machine learned information about a person who purchased the item, machine learned information about a person returning the item, and machined learned information about a condition of the item at at least one of the time of sale and at the time of return;

a conveyer system configured to automatively sort the item using a conveyer system to move the item from a counter to a respective storage area of a plurality of storage areas assigned to different product types;

perform imaging and scanning operations to determine item related information comprising at least one of a brand of the item, a product type for the item, a size of the item, a color of the item, an authentication mark made on the item, a weight of the item, and a code associated with the item; and

validate that the item is not associated with a previous return attempt based on the item related information.

10. The system according to claim 9 , wherein the programming instructions further comprise instructions to learn features and characteristics of counterfeit items which are not consistent with features and characteristics of corresponding non-counterfeit items.

11. The system according to claim 10 , wherein the programming instructions further comprise instructions to:

determine if the item is a counterfeit item based on the learned features and characteristics of counterfeit items;

allow return of the item if it is determined that the item is not a counterfeit item; and deny the return of the item if it is determined that the item is a counterfeit item.

12. The system according to claim 9 , wherein the programming instructions further comprise instructions to verify that the item's return is authorized by (A) determining if a credit card number, token or code obtained from a user matches that used to purchase the item, or (B) determine if a person shown in an image captured by a camera located by a return station matches a person shown in an image captured during a purchase transaction for the item.

13. The system according to claim 9 , wherein the programming instructions further comprise instructions to validate that the item being returned is a previously purchased item based on the item related information.

14. The system according to claim 9 , wherein the programming instructions further comprise instructions to determine a condition of the item based on contents of an image captured while the item is being returned.

15. The system according to claim 14 , wherein the programming instructions further comprise instructions to determine if the item can be resold based on the determined condition.

16. The system according to claim 14 , wherein the programming instructions further comprise instructions to determine if the condition of the item is the same or different at a time of purchase and a time of return.