Focus Adjusting Apparatus with Reliability-Based Tolerance for Irregular Subject Motion
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Solution Overview
Problem
Existing focus adjusting apparatuses face challenges in tracking moving subjects with unpredictable movements, leading to potential tracking failures and requiring user intervention, which can be difficult for inexperienced users, and do not adequately handle sudden changes in motion characteristics or erroneous tracking based on image features.
Innovation Solution
A focus adjusting apparatus and method that includes a tracking unit, prediction unit, setting unit, and determination unit to detect and predict the position of a subject's imaging plane, set tolerances based on reliability, and determine the focus adjustment area, ensuring accurate focus adjustment even with irregular movements by accounting for prediction errors and user reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If focus adjustment is performed based solely on prediction from past detection results, then tracking precision is improved for regular movements, but tracking failure occurs for unpredictable movements
Solution Approach 1:
The system performs preliminary focus adjustment based on predicted imaging plane position before actual shooting occurs. This allows the system to prepare focus settings in advance while still having the option to adjust based on actual detection results, resolving the contradiction between prediction-based precision and reliability for unpredictable movements.
Solution Approach 2:
The system compares the predicted imaging plane position with the actually detected position and uses this feedback to determine whether to apply the prediction. When the difference exceeds a threshold, the system relies on actual detection rather than prediction, thereby maintaining both precision for regular movements and reliability for unpredictable ones.
2Reliability
If user-designated tracking position is used for unpredictable movements, then tracking reliability is improved, but ease of operation deteriorates due to difficult manual tracking
Solution Approach 1:
The system automatically determines whether to use prediction or actual detection results without requiring user intervention. It self-adjusts the tracking method based on movement predictability, eliminating the need for users to manually designate tracking positions while maintaining reliability for unpredictable movements.
Solution Approach 2:
The system introduces an intermediary mechanism (the determination unit) that automatically selects between prediction-based and detection-based tracking. This mediator resolves the contradiction by enabling reliable automatic tracking without requiring direct user input, thus maintaining both reliability and ease of operation.
3Adaptability or versatility
If tracking based on image features is used, then adaptability to sudden motion changes is improved, but measurement precision deteriorates due to erroneous tracking
Solution Approach 1:
The system uses feedback from comparing predicted positions with detected positions to identify erroneous tracking. When discrepancies exceed a threshold, the system recognizes image feature-based tracking may be erroneous and adjusts accordingly, maintaining adaptability while preventing precision degradation from false tracking.
Solution Approach 2:
The system dynamically adjusts the weight given to image feature-based tracking versus prediction-based tracking based on current movement characteristics. This allows the system to adapt to sudden motion changes when they are genuine while rejecting erroneous tracking, thus balancing adaptability and precision.
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
The solution effectively prevents malfunction caused by erroneous tracking and allows for appropriate focus adjustment with subjects moving irregularly in the optical axis direction, improving tracking performance and user experience by setting appropriate tolerances based on reliability and prediction accuracy.
Implementation Method 1
an image signal that has been output from an image sensor through photoelectric conversion of light incident on the image sensor
Data Source
AI summary
In a focus adjusting apparatus, a tracking unit detects from an image signal an area of a subject to be tracked, a position of an imaging plane of the area and reliability of the position, and a prediction unit predicts a position of an imaging plane when the image signal was obtained based on a history of detected positions of imaging planes. A setting unit sets a tolerance based on the reliability, and a determination unit determines the area of the detected subject as a focus adjustment area if a difference between the predicted and detected positions is within the tolerance. The prediction unit predicts a position of an imaging plane of the subject in the focus adjustment area at a future time point.