Facial Feature Cursor Control for Peripheral-Free Display Browsing
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Solution Overview
Problem
Existing devices require hardware peripherals for browsing and are unable to determine user focus without them, leading to inefficient resource consumption and inaccurate insights.
Innovation Solution
A user device processes facial features using a neural network to calculate cursor positions based on facial movements, enabling browsing without peripherals and generating insights on user intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If hardware peripherals (mouse, touchscreen) are used for browsing, then browsing functionality is achieved, but device complexity and resource consumption increase
Solution Approach 1:
The patent replaces mechanical browsing interfaces (mouse, touchscreen) with a facial recognition-based control system. The system uses a camera to capture facial images, processes these images through neural networks to detect facial features and movements, and translates these movements into cursor control and browsing actions. This substitution eliminates the need for external hardware peripherals while maintaining browsing functionality.
Solution Approach 2:
The system creates a digital representation of the user's facial movements by capturing images with a camera and processing them through computational models. The facial feature positions and movements are copied and translated into cursor positions and browsing commands, allowing the user interface to respond to facial gestures without requiring physical contact or mechanical input devices.
2Loss of information
If hardware peripherals are required for browsing, then user input is captured, but computing resources are consumed unnecessarily when users are only observing
Solution Approach 1:
The system replaces passive hardware peripheral detection with active facial movement detection using computer vision. The camera continuously captures facial images, and neural networks process these images to detect subtle facial movements that indicate user intent. This allows the system to distinguish between active browsing (facial movements) and passive observation (static face), enabling dynamic resource management.
Solution Approach 2:
The system uses the user's own facial features as the input mechanism, eliminating the need for external peripherals. The facial recognition system naturally detects when the user is actively engaging with the content versus merely observing, allowing the system to self-regulate resource consumption based on detected user intent without requiring additional sensors or hardware.
3Adaptability or versatility
If facial browsing is implemented, then peripheral-free browsing is achieved, but device complexity increases due to neural network processing
Solution Approach 1:
The neural network model serves multiple functions: it detects facial features, tracks facial movements, determines user intent, and generates cursor control commands. This multi-functional approach consolidates what would otherwise require separate systems into a single unified model, reducing overall system complexity despite the advanced processing requirements.
Solution Approach 2:
The neural network model acts as an intermediary between the camera input and the browsing control system. It processes raw facial images and translates them into meaningful control signals, bridging the gap between biological facial movements and digital interface commands. This intermediary layer simplifies the integration of facial recognition technology into existing browsing frameworks.
Data Source
AI summary
A user device may receive an image of a user, and may process the image, with a model, to identify a face of the user and key markers of the face. The user device my process the face and the key markers, with the model, to identify features of the face, and may calculate a z-index representing a distance between the face and a display. The user device may calculate left and right face rotation along an x-axis of the display, and may calculate up and down face rotation along a y-axis of the display, based on the features. The user device may calculate an x-position and a y-position of a cursor on the display based on the left and right face rotation, the up and down face rotation, and the z-index, and may provide the x-position and the y-position of the cursor to the display.