SYSTEM AND METHOD FOR INTEGRATING VIDEO ANALYTICS AND DATA ANALYTICS/MINING

• US 20080303902A1
• Filed: 06/09/2008
• Published: 12/11/2008
• Est. Priority Date: 06/09/2007
• Status: Abandoned Application

• Current Assignee: Sensormatic Electronics LLC (Johnson Controls International plc)
• Original Assignee: Sensormatic Electronics Corporation (Johnson Controls International plc)
• Inventors: HEROLD, Amber Marsel, SHEN, Shuhai, ROMER, Kevin Douglas
• Application Number:
  US12/135,722
• Publication Number:
  US 20080303902A1
• Time in Patent Office: Days
• US Class Current: 348/143
• CPC Class Codes: G07F 19/207 Surveillance aspects at ATMs
• CPC Class Codes: G07G 3/003 Anti-theft control theft alarms G08B13/00
• CPC Class Codes: G08B 13/19615 wherein said pattern is defined by the user
• CPC Class Codes: G08B 13/19656 Network used to communicate with a camera, e.g. WAN, LAN, Internet

Abstract

A method and system detects potential suspicious behavior in a monitored facility. The monitored facility includes at least one point of transaction terminal. Video content of an activity occurring at the monitored facility and transaction data relating to a transaction processed at the transaction terminal are collected. The video content is correlated with the transaction data to produce correlated data. A set of user-defined rules are applied to the correlated data. Responsive to identifying a match between the correlated data and at least one rule of the set of user-defined rules, the transaction is determined to be potentially suspicious.

Claims

1. A method for detecting potential suspicious behavior in a monitored facility, the method comprising:

collecting video content of an activity occurring at the monitored facility;

collecting transaction data relating to a transaction processed at a point of transaction terminal;

correlating the video content with the transaction data to produce correlated data; and

applying a set of user-defined rules to the correlated data; and

responsive to identifying a match between the correlated data and at least one rule of the set of user-defined rules, determining that the transaction is potentially suspicious.

2. The method of claim 1, wherein the set of user-defined rules includes a combination of one or more video analytics rules and one or more data analytics rules.

3. The method of claim 2, further comprising:

marking the video content with a first timestamp indicating a time the activity occurred; and

marking the transaction data with a second timestamp indicating a time the transaction was processed,

wherein the video content is correlated with the transaction data by matching the first timestamp with the second timestamp.

4. The method of claim 3, wherein:

the data analytics rules include rules to determine that a return transaction has occurred; and

the video analytics rules include rules to determine that no customers are at the point of sale register.

5. The method of claim 3, wherein:

the data analytics rules include rules to determine that a cash transaction has been voided; and

the video analytics rules include rules to determine that no customers are at the point of sale register.

6. The method of claim 3, wherein:

the data analytics rules include rules to determine that no transaction has occurred; and

the video analytics rules include rules to determine that a drawer of the point of sale register is open.

7. A method of automatically identifying activities occurring at a monitored facility, the method comprising:

collecting video content of activity occurring at the monitored facility;

analyzing the video content using object recognition techniques by applying a set of video analytics rules to the collected video content;

collecting transaction data relating to one or more transactions processed by at least one point of transaction terminal within the sales facility; and

responsive to determining that the video content conforms to at least one video analytics rule of the set of video analytics rules, correlating the video content with the transaction data to provide correlated transaction data.

8. The method of claim 7, further comprising:

marking the video content with a first timestamp indicating a time the activity occurred; and

marking the transaction data with a second timestamp indicating a time the transaction was processed,

wherein the video content is correlated to the transaction data by matching the first timestamp with the second timestamp.

9. The method of claim 8, further comprising responsive to determining that the video content conforms to at least one video analytics rule of the set of video analytics rules, generating an alarm.

10. The method of claim 9, further comprising using the transaction data to determine why the video content conforms to at least one video analytics rule of the set of video analytics rules.

11. The method of claim 9, wherein the at least one video analytics rule includes a rule to determine that an amount of customers standing in a check-out line exceeds a predetermined threshold.

12. The method of claim 9, wherein the at least one video analytics rule includes a rule to determine that a duration of time that a customer has spent standing in a check-out line exceeds a predetermined threshold.

13. The method of claim 8, further comprising:

responsive to determining that the video content conforms to at least one video analytics rule of the set of video analytics rules, generating a report detailing transactions occurring while the video content conforms to at least one video analytics rule.

14. The method of claim 13, wherein the at least one video analytics rule includes a rule to determine an amount of customers entering and exiting the sales facility.

15. A system for analyzing activities occurring at a monitored facility, the monitored facility including at least one point of transaction terminal, the system comprising:

a video analytics system, the video analytics system operable to collect video content of activities occurring at the monitored facility;

a data analytics system, the data analytics system operable to collect transaction data relating to one or more transactions processed by the at least one point of transaction terminal; and

an integration server communicatively coupled to the video analytics system and the data analytics system, the integration server operable to;

correlate the video content to the transaction data to produce correlated data;

apply a set of user-defined rules to the correlated data; and

identify a match between the correlated data and at least one rule of the set of user-defined rules.

16. The system of claim 15, wherein the integration server is further operable to determine that the one or more transactions are potentially suspicious and generate an alarm, the system further comprising a client interface communicatively coupled to the integration server, the client interface operable to indicate the alarm.

17. The system of claim 16, wherein the client interface is further operable to receive the set of user-defined rules, the set of user-defined rules including a combination of one or more video analytics rules and one or more data analytics rules.

18. The system of claim 17, wherein the video content includes a first timestamp indicating the time the activity occurred and the transaction data includes a second timestamp indicating the time the transaction was processed, the integration server is further operable to correlate the video content to the transaction data by matching the first timestamp with the second timestamp.

19. The system of claim 18, wherein:

the data analytics rules include rules to determine that a return transaction has occurred; and

the video analytics rules include rules to determine that no customers are at the point of transaction terminal.

20. The system of claim 18, wherein:

the data analytics rules include rules to determine that a cash transaction has been voided; and

the video analytics rules include rules to determine that no customers are at the point of transaction terminal.