Vertical Gaze Detection via Eyelid Coverage Analysis
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Solution Overview
Problem
Current technologies lack an effective method for automatically detecting vertical gaze direction, which is essential for various applications such as gaming, power saving, and device control, particularly in camera-enabled appliances like digital still cameras, mobile phones, and laptops.
Innovation Solution
The technique involves analyzing the degree of eye lid coverage to determine the approximate direction of vertical eye gaze, allowing for actions like controlling avatars in gaming applications or initiating power save routines based on the detected gaze direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If eye gaze direction is not detected, then device control and user interaction remain manual and less efficient, but implementing gaze detection increases device complexity
Solution Approach 1:
The imaging device, originally designed for capturing images or video, is enhanced to perform multiple functions including eye gaze detection. By utilizing the existing imaging sensor and processing capabilities for both photography and gaze analysis, the device achieves multi-functionality without requiring completely separate systems, thereby improving ease of operation while controlling the increase in complexity.
Solution Approach 2:
The system automatically detects eye gaze direction and performs actions without requiring manual user input. The imaging device captures images, processes them to determine gaze direction, and triggers appropriate responses autonomously, making the device self-service oriented and significantly improving ease of operation.
2Adaptability or versatility
If traditional manual control methods are used, then device functionality is limited, but implementing automatic gaze detection requires additional processing capabilities
Solution Approach 1:
The imaging device is designed to serve multiple purposes: traditional image capture and new eye gaze detection functionality. The same imaging sensor and processing unit are utilized for both functions, allowing the device to be versatile without proportionally increasing complexity.
Solution Approach 2:
The system changes the operational parameters of the imaging device by analyzing specific features in captured images (eye position, eyelid coverage) to determine gaze direction. By modifying how the existing hardware parameters are utilized rather than adding extensive new hardware, the system achieves enhanced adaptability while managing processing complexity.
3Reliability
If eye gaze detection is implemented, then applications like gaming and power saving can be enhanced, but the measurement and detection of vertical gaze direction becomes more difficult
Solution Approach 1:
The eye region in captured images is segmented into distinct components (iris, pupil, eyelids, eyebrow) to analyze their relative positions and orientations. By dividing the complex task of gaze detection into smaller analytical segments, the system can more accurately determine vertical gaze direction despite the inherent difficulty of the measurement.
Solution Approach 2:
The system utilizes color and intensity variations in the eye region to identify different anatomical structures and their orientations. By analyzing color patterns and intensity gradients in the captured images, the system can distinguish between eye components and determine gaze direction more reliably, addressing the difficulty of vertical gaze measurement.
Data Source
AI summary
A method of detecting and applying a vertical gaze direction of a face within a digital image includes analyzing one or both eyes of a face within an acquired image, including determining a degree of coverage of an eye ball by an eye lid within the digital image. Based on the determined degree of coverage of the eye ball by the eye lid, an approximate direction of vertical eye gaze is determined. A further action is selected based on the determined approximate direction of vertical eye gaze.