STILL IMAGE SHOPPING EVENT MONITORING AND ANALYSIS SYSTEM AND METHOD

• US 20080215462A1
• Filed: 02/12/2008
• Published: 09/04/2008
• Est. Priority Date: 02/12/2007
• Status: Active Grant

• Current Assignee: Shopper Scientist LLC
• Original Assignee: Sorensen Associates LLC (TNS Group Holdings Ltd.)
• Inventors: Sorensen, Herb, Albers, David, Gibney, Michael D., Byram, Mark A., Wynne, Michael S.
• Granted Patent: US 8,873,794 B2
• Time in Patent Office: Days
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69

Abstract

The still image shopping event analysis systems and methods provided herein may implement low frequency still image sampling and perform a computer analysis of the still images captured, including discriminating differences between frames of the still images based on changes of pixels between the frames and detecting and/or analyzing one or more shopping events based on the discriminated differences between frames of the still images. The systems and methods provided herein may further count and/or analyze the shopping events based on patterns of changes between frames, including for example, numbers of customers visiting and amounts of time customers spent visiting a shopping area, whether the visit was a transitory visit or involved more detailed shopping, whether a purchase occurred, and/or which and number of item(s) purchased.

Claims

1. A still image shopping event analysis method, comprising:

capturing at a low frequency a sequence of still images of one or more monitored shopping areas; and

performing a computer analysis of the still images captured, including;

discriminating differences between frames of the still images based on changes of pixels between the frames; and

detecting and/or analyzing one or more shopping events based on the discriminated differences between frames of the still images.

2. The method of claim 1, wherein the monitored shopping areas include one or more areas of a grocery store, pharmacy, fresh meat counter, and/or deli counter.

3. The method of claim 1, wherein the still images are captured using one or more power over the Ethernet (POE) cameras that are configured to snap still images at a desired rate that is lower than a video frame rate.

4. The method of claim 1, wherein the computer analysis is carried out by an analysis computer, and the method further comprises transmitting the still images to the analysis computer via for example a wireless virtual private network (VPN) over an internet, prior to performing the computer analysis.

5. The method of claim 1, wherein performing the computer analysis of the still images further includes categorizing still images into different shopping events based on changes in pixels between frames, including constant-events during which no customer is visiting the monitored shopping area when changes in pixels between frames are below a threshold, and visiting-events during which one or more customers are visiting the monitored shopping area when changes in pixels between frames are above a threshold.

6. The method of claim 5, wherein performing the computer analysis of the still images further includes measuring duration of one or more the shopping events.

7. The method of claim 5, wherein performing the computer analysis of the still images further includes estimating a number and/or percentage of customers visited the monitored shopping area based on the number of visiting-events identified in a particular time period.

8. The method of claim 5, wherein performing the computer analysis further includes determining an entrance direction of a visiting customer during a visiting-event based on characteristics of a line graph of the visiting-event the line graph of the visiting-event plots differences between frames.

9. The method of claim 5, wherein performing the computer analysis of the still images further includes, based on duration of the visiting-events categorizing the visiting-events into transitory-events and stopping-to-shop-events, wherein during each of the visiting-events, one or more customers are passing the monitored shopping areas, and during each of the stopping-to-shop-events, one or more customers visiting the monitored shopping areas also stopped to shop.

10. The method of claim 9, wherein performing the computer analysis of the still images further includes estimating a number and/or a percentage of customers who stopped to shop in the monitored shopping areas based on number of stopping-to-shop-events occurring in a particular time period.

11. The method of claim 5, wherein performing the computer analysis of the still images further includes estimating number of visiting customers during a visiting-event based on a share of and/or number of pixels of the still images that has been changed from the still images of a constant-event, and/or the pixel changes throughout the visiting-event.

12. The method of claim 5, wherein performing the computer analysis of the still images further includes interpolating changes in pixels attributed to a change in appearance of a product region of the monitored shopping area between two constant-events as an occurrence of a purchasing-event, during which a purchase of an item located in the product region has been made by a visiting customer.

13. The method of claim 12, wherein performing the computer analysis of the still images further includes identifying an item and/or product being purchased based on position of pixels changed.

14. The method of claim 13, wherein performing the computer analysis of the still images further includes calculating total number of the items being purchased based on the number of purchasing-events during which customers have purchased the item and/or product.

15. The method of claim 14, wherein performing the computer analysis further includes identifying product stock-outs and/or pending product stock-outs of the item, and/or providing alerts regarding product stock-outs and/or pending product stock-outs of the item based on the calculated total number of the items being purchased.

16. The method of claim 12, wherein performing the computer analysis of the still images further includes identifying a number of purchasing-events that occurred in a particular time period, and estimating a number and/or percentage of customers visiting the monitored shopping area also made a purchase of an item of located in the monitored shopping area based on the number of purchasing-events.

17. The method of claim 2, wherein the method further includes tagging the still images and using the tagging information to assist the computer analysis of the still images.

18. The method of claim 17, wherein the tagging information enables single images and/or groups of images of a shopping event to be viewed to assist in the computer analysis of the shopping event.

19. A still image shopping event analysis system, comprising:

a camera configured to capture at a low frequency a sequence of still images of one or more monitored shopping areas; and

a data analysis module configured to;

perform computer analysis of the still images to discriminate differences between frames of the still images based on pixel changes; and

detect and/or analyze one or more shopping events based on the discriminated differences between frames of the still images.

20. The still image shopping event analysis system of claim 19, further comprising a still image tagging module configured to tag the still images to assist in the computer analysis of the still images.

21. The still image shopping event analysis system of claim 19, wherein the system further includes an image viewing tool configured to show a sequence of still images captured during a selected shopping event.