Gesture Pattern Analysis via Polygon Grid Text Conversion
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Solution Overview
Problem
Conventional approaches to monitoring end-user interactions with applications are insufficient, as they focus on high-level Boolean interactions and are not capable of handling the complexity and scale of user interactions with touch screens, making it difficult to analyze and understand how users interact with applications effectively.
Innovation Solution
The system converts pixel-based representations of user interface gesture patterns into text-based representations using a repetitive arrangement of polygons, allowing for more compact and flexible analysis across different devices, enabling the use of standard text correlation tools to identify similar gesture patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel-based representations of gesture patterns are used, then measurement precision is improved, but data volume and processing complexity increase significantly
Solution Approach 1:
The patent segments the continuous pixel-based gesture data into discrete grid cells. The visual display is divided into a grid of cells, and gesture patterns are represented by sequences of cell identifiers rather than individual pixel coordinates. This segmentation reduces data volume while preserving the essential spatial and temporal characteristics of gestures.
Solution Approach 2:
The patent creates an abstract copy of the gesture pattern using grid cell identifiers instead of exact pixel coordinates. This copied representation maintains the topological and sequential properties of the original gesture while significantly reducing the amount of data needed to represent it.
2Measurement precision
If pixel-based representations are used, then gesture pattern detail is improved, but ease of operation and analysis deteriorate
Solution Approach 1:
The patent introduces grid cells as an intermediary layer between the raw pixel data and the analysis process. Instead of directly analyzing pixel coordinates, the system first maps gestures to grid cell sequences, which then serve as the basis for pattern recognition and correlation analysis. This intermediary simplifies the analysis operations.
Solution Approach 2:
The patent changes the parameter representation from continuous pixel coordinates to discrete grid cell identifiers. This parameter transformation converts the gesture data into a form that is more suitable for computational analysis, pattern matching, and correlation operations while retaining the essential gesture characteristics.
3Device complexity
If conventional Boolean interaction monitoring is used, then device complexity is reduced, but measurement precision and user interaction understanding deteriorate
Solution Approach 1:
The patent transitions from static Boolean interaction states to dynamic gesture pattern sequences. Instead of merely detecting whether a button was pressed, the system captures the temporal evolution of touch points across multiple grid cells, creating a dynamic representation that preserves the flow and progression of user gestures.
Solution Approach 2:
The patent adds temporal and sequential dimensions to the interaction data. By representing gestures as sequences of grid cell identifiers over time, the system captures not just the spatial location but also the temporal progression of gestures, enabling more sophisticated analysis of user behavior patterns.
Data Source
AI summary
Facilitating analysis of user interface gesture patterns is described. In example implementations, a computing device acquires data that describes a user interface gesture pattern, such as finger movements on a touchscreen, in terms of pixels of a visual display. A repetitive arrangement of polygons, such as a grid of rectangles, is logically overlaid on the visual display. The computing device transforms the pixel-based data into polygon-based data that represents the gesture pattern in terms of polygons traversed by the gesture pattern. The computing device also converts the polygon-based data into text-based data such that the gesture pattern is represented by textual characters, such as a text string. The text string can include, for instance, a list of polygons traversed by the gesture pattern. The text-based data is forwarded to a service that can efficiently analyze relationships that may exist among multiple gesture patterns across multiple devices or end users.