Eyeglass Wearable Computer With Eye-Tracked Scene Capture
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Solution Overview
Problem
Existing personal computers, particularly those with natural user interfaces, lack the ability to see through the user's eyes, limiting their proactive assistance and requiring users to manually operate cameras, which detracts from the user experience.
Innovation Solution
A wearable computer system comprising an eyeglass frame with a scene camera and eye tracking unit that captures and processes visual data, allowing interaction via eye, hand, and voice gestures, and provides feedback through a digital personal assistant.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a personal assistant can hear and talk but cannot see, then the device can process voice commands, but the assistant cannot understand visual context and user needs
Solution Approach 1:
The system divides visual processing into two segments: an eye-tracking camera that captures only the user's gaze direction (low resolution, minimal data) and a scene camera that captures the full visual scene (high resolution). This segmentation allows the system to achieve visual awareness without requiring a single complex high-resolution camera system, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The eye-tracking data serves as an intermediary that guides the scene camera's field of view. Instead of the scene camera capturing everything simultaneously (requiring high complexity), the eye-tracking information acts as a mediator to select and prioritize what needs to be captured, enabling the system to understand visual context while managing complexity through coordinated multi-camera operation.
2Ease of operation
If a user manually operates a camera to capture moments, then the camera can be controlled precisely, but the user must split attention between recording and enjoying the experience
Solution Approach 1:
The wearable computer system performs self-service by automatically capturing moments based on eye-tracking data and scene analysis. The system monitors the user's gaze and autonomously determines when and what to record, eliminating the need for manual camera operation while maintaining accurate recording through intelligent automation that adapts to user behavior patterns.
Solution Approach 2:
The eye-tracking camera continuously monitors the user's gaze direction in advance, predicting what the user wants to capture before they manually operate the camera. This preliminary action allows the system to pre-position the scene camera or prepare recording parameters, ensuring accurate capture occurs at the optimal moment without requiring user intervention during the actual recording.
3Extent of automation
If a computer is reactive and requires user interaction, then the device can respond to commands, but the computer cannot proactively anticipate user needs
Solution Approach 1:
The system performs preliminary analysis of the visual scene and user gaze patterns before the user explicitly requests assistance. By continuously processing eye-tracking data and scene images, the computer anticipates user needs and proactively offers relevant information or actions, transforming from reactive to proactive operation through intelligent prediction algorithms.
Solution Approach 2:
The system establishes a feedback loop where eye-tracking data and scene analysis continuously inform the digital assistant's behavior. The assistant monitors user gaze patterns and scene context, adjusting its proactive assistance strategy based on real-time feedback. This feedback mechanism enables the system to learn user preferences and improve its anticipation capability while managing processing complexity through adaptive algorithms.
Data Source
AI summary
An embodiment of a Wearable Computer apparatus includes a first portable unit for data gathering and providing a natural user interface, and a second portable unit for processing the gathered data from the first unit and taking an action in respond to the received data. The first portable unit includes an eyeglass frame, at least one first scene camera disposed on the eyeglass frame for capturing at least one scene image corresponding to a field of view of a user, at least one microphone, one speaker and one LED to create a natural user interface, and at least one first processor to receive data from the data gathering units in the first portable unit and communicating that data to the second portable unit. The second portable unit is in communication with the first portable unit and includes at least one second processor configured for receiving data from the first processor. The second portable unit also includes at least one interface of a digital personal assistant that receives at least one scene image from the first portable unit and initiates an object recognition procedure to recognize an object in the at least one scene image. Based on the at least one recognized object, the digital personal assistant takes an action that may include providing a feedback to the user via light or audio.