Visual Builder Tool for Hand Gesture Creation
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Solution Overview
Problem
Current hand gesture creation tools for human-machine interfaces (HMIs) are complex and time-consuming, failing to provide a unified and reliable interaction due to their reliance on complex interfaces and the variability in hand gestures performed by different users.
Innovation Solution
A visual builder tool with a hierarchical menu-based interface that uses discrete pose and motion values to define hand gestures, generating software code for hand gestures, allowing for intuitive creation and simplifying recognition through finite state machines and gesture libraries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional gesture creation tools are used, then hand gestures can be created, but the interface becomes complex and time-consuming
Solution Approach 1:
The gesture creation process is segmented into discrete, manageable components: selecting from predefined pose values, choosing motion types, and configuring parameters. This breaks down the complex task of gesture creation into simple, sequential steps that are easier to operate.
Solution Approach 2:
The system changes the parameter representation from continuous spatial coordinates to discrete enumerated values. Gestures are defined by selecting from predefined pose values and motion types rather than specifying exact positions and trajectories, simplifying the creation process.
2Productivity
If traditional gesture recognition systems are used, then hand gestures can be recognized, but intensive machine learning and computer vision processing is required
Solution Approach 1:
The system replaces complex machine learning and computer vision processing with a rule-based recognition engine. Instead of using intensive algorithms to interpret continuous hand motion data, the system matches discrete pose values and motion types against predefined gesture patterns, significantly reducing computational energy consumption.
3Reliability
If continuous hand gesture data is used, then accurate gesture representation is achieved, but sensitivity to user variability increases
Solution Approach 1:
The system transforms continuous hand gesture parameters into discrete enumerated values. By quantizing hand poses, finger configurations, and motion types into predefined categories, the system reduces sensitivity to variations in user performance while maintaining reliable gesture recognition.
Solution Approach 2:
The system enforces homogeneity by requiring gestures to conform to standardized discrete pose values and motion types. This normalization across different users and gestures improves reliability by providing consistent recognition criteria.
4Manufacturing precision
If detailed hand gesture features are captured, then precise gesture definition is achieved, but creation time increases
Solution Approach 1:
The system performs preliminary action by pre-defining pose values, motion types, and gesture templates. Creators only need to select from these pre-prepared options rather than defining every detail from scratch, achieving precise gesture definition with minimal creation time.
Data Source
AI summary
A system for creating hand gestures representations, comprising an interface for interacting with a user, a storage storing a plurality of discrete pose values and discrete motion values, a memory storing a gesture visual builder code, one or more processors coupled to the interface, storage and memory to execute the gesture visual builder code allowing the user to create hand gesture. The gesture visual builder code comprising code instructions to present the user with a GUI which displays a hierarchical menu driven interface, code instructions to receive iteratively user instructions from the user using the hierarchical menu driven interface, for creating a logical sequence of hand gesture by defining one or more hand pose features records and hand motion features records and code instructions to generate a code segment defining the one or more hand pose/motion features records through the discrete pose/motion values respectively.