Edge Input Probability Assignment for Gesture Disambiguation
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Solution Overview
Problem
Portable electronic devices face challenges in accurately interpreting ambiguous user inputs, such as touch or swipe gestures, especially when they can be interpreted in multiple ways, leading to incorrect actions and user frustration.
Innovation Solution
The device dynamically assigns probabilities to possible inputs based on the time between current and previous inputs, the current view, and the location of the input on the screen, particularly at the edge region, to determine the most likely intended action, thereby differentiating between actions like scrolling and closing applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the device uses a touch-sensitive screen to detect user inputs, then the ease of operation is improved, but the reliability of input interpretation deteriorates due to ambiguous gestures
Solution Approach 1:
The system changes the parameter of input interpretation by dynamically adjusting the weight or probability assigned to different possible inputs based on contextual parameters such as current application state, recent input history, and gesture characteristics. This allows the same physical gesture to be interpreted differently depending on the context, resolving ambiguity while maintaining ease of use.
Solution Approach 2:
The system implements feedback by analyzing the sequence of inputs and using the current state to inform the interpretation of subsequent inputs. By considering the temporal relationship between inputs and the current application state, the system provides more reliable interpretation of ambiguous gestures while maintaining the simplicity of touch interaction.
2Productivity
If the device interprets edge region inputs as application closing gestures, then the productivity is improved through quick application switching, but the manufacturing precision of input detection deteriorates due to false gesture recognition
Solution Approach 1:
The system applies local quality by treating different regions of the display with different interpretation rules. Edge regions are assigned higher probability for application closing gestures, while central regions are assigned higher probability for scrolling gestures. This spatial differentiation allows the system to maintain high productivity for intended gestures while reducing false recognition.
Solution Approach 2:
The system dynamically changes the interpretation parameters for edge region inputs based on the current application state and recent input patterns. When scrolling is detected in the recent history, the system adjusts parameters to favor scrolling interpretation even for edge inputs, reducing false application closing recognition while maintaining quick switching capability when appropriate.
3Productivity
If the device quickly processes consecutive user inputs, then the productivity is improved, but the reliability of input differentiation deteriorates due to insufficient time for accurate gesture recognition
Solution Approach 1:
The system performs preliminary action by pre-defining multiple possible interpretations for each input and pre-calculating their probabilities based on the current state. When a new input arrives, the system quickly updates the probabilities rather than performing complex analysis from scratch, enabling fast processing of consecutive inputs while maintaining reliable differentiation.
Solution Approach 2:
The system uses feedback from the sequence of inputs to improve interpretation reliability. By analyzing the temporal pattern and using the current state informed by previous inputs, the system can quickly and accurately differentiate between consecutive gestures even when they occur in rapid succession, maintaining both productivity and reliability.
Data Source
AI summary
An apparatus, the apparatus comprising at least one processor, and at least one memory including computer program code, the at least one memory and the computer program code configured, with the at least one processor, to cause the apparatus to perform at least the following: differentiate between two or more current possible inputs associated with a particular region of a user interface by dynamically assigning respective probabilities to two or more of the current possible inputs, wherein the dynamic assignment of the probabilities is based on at least one or more of: the time between the two or more current possible inputs and one or more previous inputs in the current view; the current view in which the two or more current possible inputs are received; the two or more current possible inputs being received at an edge region of a display showing the current view; and a specific displayed user interface element associated with the particular region, the particular region being an edge region of a display of the user interface.