Illumination-Driven Pupil Tracking for Hands-Free Intent Detection
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Solution Overview
Problem
Existing systems struggle to accurately determine user intent during interaction with electronic content without requiring explicit gestures or inputs, limiting the ability to provide tailored and engaging user experiences.
Innovation Solution
The system assesses physiological data, such as gaze characteristics and illumination responses, to predict interaction events by analyzing pupil dilation, stable gaze direction, and scene context, using machine learning to improve interaction event detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If explicit gestures or inputs are required to determine user intent, then interaction accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The patent replaces mechanical input devices (mouse, keyboard, touch screen) with a physiological detection system that uses camera-based eye tracking and pupil analysis. The system captures images of the user's eye, detects pupil position and diameter changes, and determines intent to select interaction elements without requiring physical gestures or inputs.
Solution Approach 2:
The system enables users to interact with content through their natural physiological responses (eye movements, pupil dilation) rather than requiring learned gestures or explicit inputs. The user's own biological signals serve as the interaction mechanism, making the system more intuitive and accessible.
2Adaptability or versatility
If physiological data collection is implemented, then user experience personalization is improved, but device complexity increases
Solution Approach 1:
The system uses a standard camera component already present in most electronic devices to capture eye images. This multi-functional approach allows the camera to serve both its traditional imaging purpose and the additional function of physiological data collection for intent detection, avoiding the need for specialized sensors.
Solution Approach 2:
The patent introduces software algorithms as an intermediary that processes raw camera images to extract physiological signals. The image processing pipeline includes detecting eye contours, locating the pupil, measuring pupil diameter, and tracking pupil position - all through computational methods that bridge the gap between simple image capture and complex physiological interpretation.
3Productivity
If pupillary response analysis is used to detect interaction events, then interaction event detection accuracy is improved, but measurement precision requirements increase
Solution Approach 1:
The system performs preliminary processing by detecting the eye contour and establishing a coordinate system before measuring pupil characteristics. The method first identifies the eye boundary, then uses this information to accurately locate and measure the pupil within the eye region, ensuring precise measurements even in varying image conditions.
Solution Approach 2:
The system continuously monitors pupil diameter and position changes over time, using temporal feedback to distinguish genuine pupillary responses from measurement noise. By tracking the dynamic changes in pupil characteristics and comparing them against expected physiological response patterns, the system improves detection reliability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables hands-free interaction with electronic content, enhances user experience by providing personalized and accurate responses to user intent, and supports accessibility for individuals with disabilities.
Implementation Method 1
a user's pupillary response to a visual characteristic of content presented by the device, the user's intent to interact with the content
Implementation Method 2
a user's eye gaze characteristics in response to an interaction element presented by the device
Data Source
AI summary
Various implementations disclosed herein include devices, systems, and methods that determine an interaction event during presentation of an interaction element. For example, an example process may include obtaining physiological data associated with a pupil during presentation of an interaction element, determining, based on the obtained physiological data, a pupillary response during the presentation of the interaction element, determining that the pupillary response corresponds to attention response characteristics associated with attention of a region of the regions of the interaction element based on the different illumination characteristics of the regions, and determining an interaction event during the presentation of the interaction element based on determining that the pupillary response corresponds to directing attention to the region during the presentation of the interaction element.