3D User Interface Gaze-and-Gesture Selection to Cut Interaction Load
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Solution Overview
Problem
Existing methods for interacting with virtual, augmented, and extended reality environments are cumbersome, inefficient, and complex, leading to a significant cognitive burden on users and inefficient use of battery-operated devices.
Innovation Solution
The implementation of improved user interfaces and methods that utilize gaze and hand tracking, along with tactile and audio feedback, to enhance interaction efficiency and intuitiveness in three-dimensional environments, including the use of gaze inputs to activate user interface objects and hand gestures to navigate and select items, and adjusting visual prominence of interface elements based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional input devices and interfaces are used to interact with virtual/augmented/extended reality environments, then basic interaction functionality is achieved, but user interaction efficiency is low and cognitive burden is high
Solution Approach 1:
The patent replaces conventional mechanical input devices (keyboards, mice, joysticks) with direct neural control through BCIs and natural gesture recognition. Users can select and manipulate virtual objects by thinking about desired actions or performing simple hand gestures, eliminating the need for complex mechanical interfaces and significantly improving interaction efficiency while reducing cognitive load.
Solution Approach 2:
The system automatically detects user intent through neural signals and gestures, then executes appropriate actions without requiring explicit step-by-step commands. The interface adapts to user behavior patterns, predicting desired actions and presenting relevant options, thereby reducing the number of interactions needed and improving overall productivity.
2Reliability
If multiple input steps are required to achieve desired outcomes in virtual environments, then precise control is achieved, but interaction time increases and energy consumption increases
Solution Approach 1:
The system continuously monitors neural signals and gesture patterns to predict user intent before explicit selection occurs. By pre-loading and pre-positioning relevant virtual objects and controls based on predicted needs, the system reduces the number of steps required to achieve desired outcomes while maintaining precise control through confirmatory neural or gesture inputs.
Solution Approach 2:
The interface provides real-time feedback by displaying detected neural intent and recognized gestures, allowing users to confirm or correct system interpretations. This feedback loop ensures precise control while minimizing interaction time by enabling quick corrections without requiring full re-sequence of commands.
3Productivity
If conventional interfaces are used in battery-operated devices, then basic functionality is maintained, but energy efficiency is poor due to prolonged interaction times
Solution Approach 1:
By replacing manual manipulation of conventional input devices with direct neural control and gesture recognition, the system dramatically reduces interaction time. Although BCIs require processing power, the overall energy consumption is reduced because the system achieves task completion in fewer seconds, and low-power gesture recognition can be performed using the device's existing camera and motion sensors.
Solution Approach 2:
The system employs periodic sampling of neural signals and gestures rather than continuous high-power processing. Interaction modes are activated only when needed, with the system transitioning between low-power standby states and active processing states based on detected user engagement, thereby optimizing battery efficiency while maintaining high interaction speed when in use.
Data Source
AI summary
A computer system displays a first view of a three-dimensional environment, including a first and second user interface objects at distinct first and second positions. While displaying the first view, the computer system detects a first gaze input directed to a first region in the three-dimensional environment corresponding to the first position. While detecting the first gaze input, the computer system detects first movement of a hand meeting first gesture criteria. In accordance with a determination that the first movement is detected after the first gaze input meets first gaze criteria requiring the gaze to be held at the first region for at least a first preset extended amount of time, the computer system selects the first user interface object; and in accordance with a determination that the first movement is detected before the gaze meeting the first gaze criteria, the computer system forgoes selecting the first user interface object.