Image Capture Subject Selection Using User Eye Recognition
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Solution Overview
Problem
Existing image capture systems with line of sight detection functions struggle to accurately select a main subject area due to individual differences in user intent, leading to degraded focus detection accuracy.
Innovation Solution
An image capture apparatus and control method that utilize a recognition unit to identify users based on eyeball images, selecting a main subject area from detected subjects using stored information associated with the recognized user, thereby enhancing focus detection accuracy by accounting for user-specific preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If line of sight detection is used to select focus detection area, then ease of operation is improved, but measurement precision deteriorates due to individual differences in user intent
Solution Approach 1:
The system performs preliminary subject detection and stores candidate subject information before the actual capture moment. When line of sight detection is performed, the system refers to these pre-detected subjects and their associated user preferences to quickly determine the main subject area, combining the convenience of eye control with accurate subject selection based on historical data.
Solution Approach 2:
The system uses stored information about subjects captured in the past and associated with the user as feedback to improve line of sight detection accuracy. By analyzing historical capture data and user preferences, the system refines its understanding of which areas the user intends to focus on, thereby improving measurement precision while maintaining ease of operation.
2Adaptability or versatility
If user recognition based on eyeball image is implemented, then adaptability is improved, but device complexity increases
Solution Approach 1:
The eyeball image processing system serves multiple functions: it detects line of sight direction for focus area selection, recognizes the user through iris patterns, and retrieves associated preference information. By making the eyeball image analysis multi-functional, the system achieves high adaptability without proportionally increasing device complexity, as the same hardware components perform multiple tasks.
Solution Approach 2:
The system automatically performs user recognition and retrieves stored preference information without requiring explicit user input or configuration. The eyeball image itself serves as both the line of sight detection signal and the user identification key, allowing the system to self-configure based on the captured image data.
Data Source
AI summary
An image capture apparatus detects a subject in a captured image. The image capture apparatus further recognizes its user based on an eyeball image of the user. The image capture apparatus then selects a main subject area from among the detected subject areas, based on information regarding subjects captured in the past and stored being associated with the recognized user.