Group Leader Identification via Payment Gesture Recognition
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Solution Overview
Problem
Current surveillance technologies in retail settings lack the ability to effectively identify and analyze the leader of a group for improved understanding and comparison of customer experience metrics, such as dining area cleanliness and queue management, which are crucial for enhancing customer experience and operational efficiency.
Innovation Solution
A method is developed to identify the leader of a group in a retail or restaurant setting by recognizing payment gestures through video analysis, using feature models generated from visual data, and designating the person making the payment gesture as the leader, allowing for the analysis of associated events and characteristics like entry, exit, and order timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If surveillance video is used to monitor customer spaces, then customer experience metrics can be captured, but the ability to identify and analyze group leaders is lost
Solution Approach 1:
The system segments groups of people into individual detectable entities and identifies specific roles (leader vs. follower) within each group. By breaking down the group dynamics into identifiable components through payment gesture detection, the system can now measure and analyze customer experience metrics with precise attribution to specific individuals and their roles.
2Productivity
If general crowd monitoring is implemented, then overall customer flow is tracked, but individual customer behavior analysis is insufficient
Solution Approach 1:
The payment gesture detection system serves as an intermediary that bridges general crowd monitoring and individual behavior analysis. By detecting payment gestures as a key event, the system identifies group leaders and uses them as mediators to link overall customer flow data with detailed individual behavior metrics, enabling both aggregate and granular analysis simultaneously.
3Measurement precision
If payment gesture recognition is added to surveillance systems, then group leader identification is achieved, but system complexity increases
Solution Approach 1:
The surveillance system uses existing payment infrastructure and gestures that customers already perform naturally during transactions. Rather than adding complex tracking devices or changing customer behavior, the system leverages the payment gesture itself as the identification mechanism, allowing the system to identify group leaders through already-present customer actions and existing payment technology.
Data Source
AI summary
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.).