Personalized Gesture Dictionary Assignment
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Solution Overview
Problem
Existing computing systems face challenges in providing a personalized user experience due to universal input systems that do not adapt to individual user preferences, making it difficult for users to intuitively control applications with gestures that correspond to actual physical motions.
Innovation Solution
A gesture-based system that assigns a personalized gesture dictionary to each user based on their unique gesture patterns, captured in real-time through a combination of capture devices and processors, allowing users to control applications with natural movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a universal input system is used for all users, then the system is simple to implement and maintain, but it does not provide personalized user experience and requires users to learn non-intuitive controls
Solution Approach 1:
The system performs preliminary gesture capture and analysis during a calibration phase before actual use. The capture device records user gestures, and the processor analyzes them to create a personalized gesture dictionary that maps natural user movements to application commands, preparing the personalized control scheme in advance.
Solution Approach 2:
The system automatically captures and analyzes user gestures without requiring manual programming or configuration by the user. The processor autonomously processes the captured gesture data to generate personalized gesture dictionaries, allowing the system to self-configure for each user based on their natural movement patterns.
2Ease of operation
If traditional controls like keyboards and mice are used, then the system is easy to implement, but users face a learning curve and controls do not correspond to actual physical actions
Solution Approach 1:
The system replaces traditional mechanical input devices (keyboards, mice) with a capture device that detects natural human gestures in physical space. The processor translates these gestures into application controls, substituting mechanical interaction with motion-based interaction that mirrors real-world actions.
Solution Approach 2:
The system changes the parameter of input method from discrete key presses or mouse clicks to continuous natural motion gestures. By capturing and analyzing gesture parameters such as position, velocity, and trajectory, the system enables controls that correspond to actual physical actions rather than abstract button combinations.
3Adaptability or versatility
If users are allowed to manually adjust command definitions for personalization, then personalized experience is achieved, but the task becomes laborious and users may not remember the changes
Solution Approach 1:
The system automatically captures and analyzes user gestures without requiring manual programming or configuration by the user. The processor autonomously processes the captured gesture data to generate personalized gesture dictionaries, allowing the system to self-configure for each user based on their natural movement patterns.
Solution Approach 2:
The system provides real-time feedback during the calibration process by monitoring user gestures and adjusting the gesture dictionary accordingly. This feedback loop allows the system to learn from user corrections and refinements, making the personalization process intuitive and easy to control.
Data Source
AI summary
Techniques for assigning a gesture dictionary in a gesture-based system to a user comprise capturing data representative of a user in a physical space. In a gesture-based system, gestures may control aspects of a computing environment or application, where the gestures may be derived from a user's position or movement in a physical space. In an example embodiment, the system may monitor a user's gestures and select a particular gesture dictionary in response to the manner in which the user performs the gestures. The gesture dictionary may be assigned in real time with respect to the capture of the data representative of a user's gesture. The system may generate calibration tests for assigning a gesture dictionary. The system may track the user during a set of short gesture calibration tests and assign the gesture dictionary based on a compilation of the data captured that represents the user's gestures.