Eye Gaze Controlled Indicia Scanning Autofocus
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current smartphone-based indicia scanning systems face challenges in speed and accuracy due to time-consuming autofocus routines, especially under poor lighting conditions and excessive motion, which hinder efficient barcode scanning.
Innovation Solution
A portable computer system equipped with both front-facing eye gaze detection and rear-facing imaging capabilities, allowing the processor to determine the user's gaze coordinates and dynamically configure the camera system for faster and more accurate indicia decoding by focusing on the region of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If autofocus routines are used to get the barcode into focus, then the scanning system can achieve accurate focus, but the scanning time increases significantly
Solution Approach 1:
The system performs preliminary actions by using eye gaze detection to predict the region of interest before the actual scanning occurs. The gaze tracking system continuously monitors user eye movements and pre-positions the focus and exposure settings based on where the user is looking, eliminating the need for time-consuming autofocus routines when the user gazes at a barcode.
Solution Approach 2:
The eye gaze detection system acts as an intermediary between the user and the camera system. Instead of relying on traditional autofocus algorithms that analyze the entire image, the gaze system provides direct feedback about user intent, allowing the processor to immediately configure camera parameters for the specific region the user is interested in, significantly reducing focus acquisition time.
2Adaptability or versatility
If traditional autofocus routines are used, then the system can handle various lighting conditions, but the scanning process is hampered by excessive motion and poor lighting
Solution Approach 1:
The system applies local quality by configuring camera parameters specifically for the region of interest identified through eye gaze detection. Instead of attempting to optimize focus and exposure for the entire image frame, the processor adjusts settings only for the small area where the user is looking, making the system more reliable under motion and poor lighting conditions by concentrating resources on the relevant region.
Solution Approach 2:
The system performs preliminary configuration of exposure and focus settings based on eye gaze data before the actual image capture. This pre-configuration allows the camera to be optimally set up for the specific lighting conditions in the region of interest, improving reliability when scanning under challenging conditions by eliminating the delay and uncertainty of post-capture autofocus adjustments.
3Productivity
If the entire image is scanned for indicia, then all potential barcodes can be detected, but the decoding time increases due to processing the whole image
Solution Approach 1:
The system segments the image processing task by using eye gaze detection to identify and isolate the region of interest containing the barcode. Instead of processing the entire image frame, the processor focuses decoding algorithms only on the segmented area where the user is looking, significantly reducing decoding time while maintaining the ability to detect all potential barcodes in the user's field of view.
Solution Approach 2:
The system performs preliminary identification of the barcode location through eye gaze tracking before initiating the decoding process. This pre-localization allows the system to prepare decoding parameters and focus computational resources in advance, reducing the time required to decode the barcode while ensuring that the correct region is targeted for scanning.
Data Source
AI summary
By tracking a user's eyes, an indicia scanning system can make educated guesses as to what the user is interested in. This insight could be useful in dynamically configuring a camera system, configuring an indicia decoding process or even as a method to select data that the user is interested in.