Eyeball Detection Device Using Distance-Based Search Prediction
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Solution Overview
Problem
Conventional eye-gaze tracking devices face long processing times due to the need to search for both left and right eyeball images from a face image, even if one is lost, which is also a challenge in face recognition systems.
Innovation Solution
An eyeball detection device that calculates distances between the subject and the imaging device, and between the eyeballs, allowing for efficient search and detection of one eyeball image and subsequent prediction of the other's position based on these distances, reducing processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the device searches for both left and right eyeball images from the face image using conventional methods, then the detection reliability is maintained, but the processing time becomes excessively long
Solution Approach 1:
The system performs preliminary detection of one eyeball image first, then uses the detected position and distance information to predict and narrow down the search area for the other eyeball. This preliminary action reduces the overall search time while maintaining detection reliability by guiding the subsequent search more efficiently.
Solution Approach 2:
The system introduces distance information (first-type distance from imaging device to face, and second-type distance between eyeballs) as an intermediary parameter to facilitate the eyeball detection process. This intermediary information enables the system to predict eyeball positions and reduce search areas without compromising detection accuracy.
2Measurement precision
If the device performs a comprehensive search for both eyeball images from the entire face image, then the detection accuracy is maintained, but the device complexity increases
Solution Approach 1:
The system segments the eyeball detection process into two phases: first detecting one eyeball image, then using that result to guide the search for the other eyeball. This segmentation reduces the overall search complexity by dividing the comprehensive search into targeted, sequential operations while maintaining detection accuracy.
Solution Approach 2:
The system changes the search parameters dynamically based on detected distance information. By adjusting the search area and methodology based on the first-type and second-type distances, the system reduces processing complexity while preserving detection accuracy through adaptive parameter modification.
Data Source
AI summary
An eyeball detection device includes an imaging device that obtains a face image which includes the left and right eyeball images of the target person; a first distance calculating unit that calculates a first-type distance representing the distance between the target person and the imaging device; and an eyeball searching unit that performs a search for the left and right eyeball images from the face image and, when only one of the left and right eyeball images of the target person is detected, searches for the other eyeball image of the target person based on the search result regarding the already-detected eyeball image as obtained by the eyeball detecting unit, based on the first-type distance, and based on a second-type distance representing the distance between the left and right eyeballs of the target person.