Single-Hand Gesture Scrolling for AR Content Review
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Solution Overview
Problem
Existing technologies face challenges in efficiently controlling and interacting with virtual elements on display using hand gestures, particularly in augmented and virtual reality environments, due to the complexity and processing intensity of hand and finger recognition and tracking.
Innovation Solution
A wearable device with integrated cameras and a touch-sensitive input device detects hand gestures to control the presentation of virtual elements on a display, utilizing computer vision algorithms for real-time tracking and interaction, enabling intuitive navigation and selection through predefined gestures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If hand gesture detection is implemented in augmented reality systems, then user interaction capability is improved, but processing complexity and computational load increase
Solution Approach 1:
The hand gesture recognition system divides the complex task into multiple processing stages: capturing video frames, detecting hand regions, extracting finger joint coordinates, recognizing gesture patterns, and triggering corresponding actions. This segmentation reduces the computational burden at each stage while maintaining overall recognition accuracy.
Solution Approach 2:
The system performs preliminary hand detection and finger joint identification before full gesture recognition. By pre-processing the video data to locate hand regions and extract key point coordinates in advance, the system prepares data structures that facilitate faster and more accurate gesture classification during actual interaction.
2Speed
If real-time hand gesture tracking is implemented, then responsiveness to user input is improved, but processing time and computational resources increase
Solution Approach 1:
The system processes hand gestures at specific frame intervals rather than continuously analyzing every video frame. By periodically sampling hand positions and gesture states at optimized intervals, the system maintains responsive interaction while reducing the total computational workload and processing time required for real-time tracking.
Solution Approach 2:
The system focuses computational resources on detecting only the essential finger joint coordinates needed for gesture recognition rather than processing entire hand regions or all video frame details. This partial action approach processes only the critical data points necessary for gesture identification, minimizing processing time while maintaining recognition accuracy.
3Measurement precision
If multiple finger coordinate detections are implemented, then gesture recognition accuracy is improved, but measurement complexity increases
Solution Approach 1:
The system applies different detection precision levels to different finger joints based on their importance for gesture recognition. Critical joints that define gesture identity are detected with higher precision, while less critical joints use standard detection accuracy. This localized quality approach maintains overall gesture recognition accuracy while reducing the total complexity of coordinate detection across all fingers.
Solution Approach 2:
The finger coordinate detection system uses a unified algorithm that can identify all finger joint types (tip, middle, base joints) through a single detection process. This universal detection method handles multiple finger coordinates simultaneously using the same computational approach, reducing the complexity that would arise from implementing separate detection routines for each joint type.
Data Source
AI summary
Systems, devices, media, and methods for controlling the presentation of virtual or graphical elements on a display in response to hand gestures detected by an eyewear device that is capturing frames of video data with its camera system. An image processing system detects hand shapes in the video data and determines whether it matches a predefined hand gesture. Each predefined hand gesture is associated with an action; for example, a leafing gesture is associated with a scrolling action. The system controls the display of virtual elements, in accordance with the associated action. In an example hand shapes that includes flexing and extending the fingers of a single hand severally and continually in a leafing motion, the matching predefined leafing gesture is associated with a scrolling action, which displays the series of items in a display order, sequentially and in accordance with the detected speed of the moving fingers.