Vision System Queue Management via Zone Segmentation
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Solution Overview
Problem
Conventional vision systems for queue management in retail stores are computationally expensive and inaccurate, particularly in detecting and tracking multiple queues or non-straight queues, leading to inefficient queue management and potential health risks, which can deter customers and impact sales.
Innovation Solution
A vision system that receives data frames from cameras, identifies queue spaces, tracks individuals, calculates dwell time, and generates alerts when dwell time exceeds a threshold, allowing for real-time adjustments to queue management based on queue delay indications and switching events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional vision systems use Region of Interest (ROI) to calculate queue length and waiting time, then queue management can be implemented, but the system becomes computationally expensive and complex with reduced accuracy in certain situations
Solution Approach 1:
The patent segments the monitoring area into multiple defined queue zones rather than treating the entire ROI as a single analysis unit. Each zone can be independently analyzed for queue metrics, which reduces computational complexity while maintaining measurement accuracy. The segmentation allows the system to focus processing power on specific queue areas rather than the entire field of view.
Solution Approach 2:
The patent introduces intermediate detection elements such as virtual queue lines and zone boundaries that act as mediators between the camera view and the queue measurement algorithm. These intermediaries simplify the computational task by providing clear geometric references for determining queue length and waiting time, reducing the complexity of image processing while improving measurement consistency.
2Measurement precision
If conventional vision systems use Region of Interest (ROI) to calculate queue metrics, then queue management is possible, but accuracy deteriorates when there are multiple queues or non-straight queues in the ROI
Solution Approach 1:
The patent divides the monitoring space into multiple distinct queue zones, each capable of being independently configured and analyzed. This segmentation enables the system to accurately track multiple separate queues simultaneously, as well as handle non-straight queue configurations by defining zones that follow the actual queue path geometry rather than assuming straight-line queues.
Solution Approach 2:
The patent implements dynamic zone definitions that can adapt to different queue configurations. The queue zones can be configured to follow non-straight paths and can dynamically adjust to accommodate multiple queues of varying shapes and orientations, improving the system's versatility in handling diverse retail environments without sacrificing measurement accuracy.
3Productivity
If queue management is implemented using conventional methods, then some queue monitoring is achieved, but customer safety and satisfaction deteriorate due to long queues and health risks
Solution Approach 1:
The patent implements real-time feedback mechanisms that continuously monitor queue metrics and provide immediate alerts when thresholds are exceeded. The system calculates dwell time and generates queue delay indications that trigger notifications to staff, enabling rapid response to growing queues. This feedback loop allows for dynamic queue management adjustments that prevent health risks and customer dissatisfaction by addressing queue issues before they become critical.
Solution Approach 2:
The patent employs preliminary threshold setting and predictive alerting that enables proactive queue management. By establishing predetermined queue length and dwell time thresholds, the system can issue early warnings before queues reach dangerous levels. This preliminary action allows retail staff to take preventive measures such as opening additional registers or redirecting customers before health risks or significant customer dissatisfaction occur.
Data Source
AI summary
Example implementations include a method, apparatus and computer-readable medium for tracking queue space events, comprising receiving a plurality of data frames from a camera capturing a view of an environment. The implementations further include identifying in the plurality of data frames at least one queue space of the environment, tracking a position of a first person in the plurality of data frames, and calculating a dwell time of the first person when detecting that the position of the first person is in the at least one queue space. Additionally, the implementations include generating a queue delay indication in response to determining that the dwell time exceeds a threshold dwell time, and generating an alert that an attribute of the at least one queue space needs to be modified in response to determining that more than a threshold amount of queue delay indications have been generated within a period of time.