Queue group leader identification
A system and method to identify the leader of a group in a retail, restaurant, or queue-type setting (or virtually any setting) through recognition of payment gestures. The method comprises acquiring initial video of a group, developing feature models for members of the group, acquiring video at a payment location, identifying a payment gesture in the acquired video, defining the person making the gesture as the leader of the group, and forwarding/backtracking through the video to identify timings associated with leader events (e.g., entering, exiting, ordering, etc.).
1. A method of monitoring a customer space comprising:
obtaining a video stream from an overhead camera capturing video from at least one region of interest, the region of interest associated with a type of payment gesture;
detecting motion within the at least one region of interest;
creating a representation of the motion occurring within the at least one region of interest;
detecting the payment gesture based on the representation;
obtaining visual data comprising image frames from a counter view camera;
generating feature models for members of at least one group within the customer space using the image frames from the counter view camera;
associating the payment gesture with a member of the at least one group; and
designating a leader of the group as the member associated with the payment gesture;
wherein the payment gesture includes tender of payment at a payment station within the customer space; and
wherein the payment gesture includes at least one of swiping a credit card or presenting cash at a payment station within the customer space.
2. The method of claim 1 further comprising, after designating the leader, analyzing the visual data to determine the timing of at least one event involving the leader.
3. The method of claim 2 , wherein the at least one event includes one or more of the leader entering the customer space, the leader exiting the customer space, or the leader placing an order.
4. The method of claim 1 further comprising, after designating the leader, analyzing the visual data before or after the payment gesture to identify at least one characteristic of the leader's experience within the retail space.
5. The method of claim 4 , wherein the at least one characteristic includes position within the group, location within the retail space, or action taken by the leader.
6. The method of claim 1 , wherein the generating feature models includes using a face detection algorithm.
7. The method of claim 1 , wherein the obtaining visual data includes obtaining overhead visual data comprising image frames of a payment station, and using said overhead visual data to identify the payment gesture including at least one of swiping a credit card or presenting cash.
8. The method of claim 7 , wherein the associating the payment gesture with a member of the at least one group includes determining the member making the payment gesture based on location information associated with the visual data.
9. The method of claim 1 , wherein the obtaining visual data includes recording images with an overhead camera, and wherein the designating a leader of the group as the member associated with the payment gesture is based solely on the payment gesture as identified in the images.
10. A non-transitory computer-readable medium having stored thereon computer-executable instructions for monitoring a customer space, the instructions being executable by a processor and comprising:
obtaining a video stream from an overhead camera capturing video from at least one region of interest, the region of interest associated with a type of payment gesture;
detecting motion within the at least one region of interest;
creating a representation of the motion occurring within the at least one region of interest;
detecting the payment gesture based on the representation;
obtaining visual data comprising image frames from a counter view camera;
generating feature models for members of at least one group within the customer space using the image frames from the counter view camera;
associating the payment gesture with a member of the at least one group; and
designating a leader of the group as the member associated with the payment gesture;
wherein the payment gesture includes at least one of swiping a credit card or presenting cash at a payment station within the customer space; and
wherein the camera is an overhead camera.
11. The non-transitory computer-readable medium as set forth in claim 10 , wherein the instructions further comprise, after designating the leader, analyzing the visual data to determine the timing of at least one event involving the leader.
12. The non-transitory computer-readable medium as set forth in claim 10 , wherein the at least one event includes one or more of the leader entering the customer space, the leader exiting the customer space, or the leader placing an order.
13. The non-transitory computer-readable medium as set forth in claim 10 , wherein the instructions further comprise, after designating the leader, analyzing the visual data before or after the payment gesture to identify at least one characteristic of the leader's experience within the retail space.
14. The non-transitory computer-readable medium as set forth in claim 13 , wherein the at least one characteristic includes, position within the group, location within the retail space, or action taken by the leader.
15. A system for monitoring a customer space comprising:
at least one overhead optical sensor for obtaining a video stream capturing video from at least one region of interest, the region of interest associated with a type of payment gesture; and
a central processing unit including a processor and a non-transitory computer-readable medium having stored thereon computer-executable instructions for monitoring a customer space executable by the processor, the instructions comprising:
receiving visual data of the region of interest over a period of time from the overhead optical sensor;
detecting motion within the at least one region of interest;
creating a representation of the motion occurring within the at least one region of interest;
detecting the payment gesture based on the representation;
obtaining visual data from at least one oblique sensor;
generating feature models for members of at least one group within the customer space using the visual data from the oblique sensor;
associating the payment gesture with a member of the at least one group; and
designating a leader of the group as the member associated with the payment gesture;
wherein the payment gesture includes at least one of swiping a credit card or presenting cash at a payment station within the customer space.
16. The system of claim 15 , wherein the instructions further comprise, after designating the leader, analyzing the visual data to determine the timing of at least one event involving the leader.
17. The system of claim 16 , wherein the at least one event includes one or more of the leader entering the customer space, the leader exiting the customer space, or the leader placing an order.
18. The system of claim 15 , wherein the instructions further comprise, after designating the leader, analyzing the visual data before and after the payment gesture to identify at least one characteristic of the leader's experience within the retail space.
19. The system of claim 18 , wherein the at least one characteristic includes, position within the group, location within the retail space, or action taken by the leader.