Autofocus Method Using Face Detection and Sharpness Thresholds
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Solution Overview
Problem
Conventional autofocus systems in image acquisition devices, such as those in mobile phones and cameras, face challenges in quickly determining optimal focus, especially in low-light conditions and when dealing with subjects that do not have distinct features, leading to slow and unpleasant 'focus hunting' processes.
Innovation Solution
The method employs a sharpness measure based on image acquisition parameters like distance to the subject and ambient light level to determine if a lens sweep is required, switching between face detection autofocus and other methods, and uses stability of face detection to decide between autofocus modes, thereby minimizing unnecessary focus adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional autofocus systems perform lens sweeps to determine optimal focus, then focus accuracy is improved, but acquisition time increases and user experience deteriorates
Solution Approach 1:
The system performs preliminary face detection and estimates the subject distance using known facial dimensions before initiating focus adjustment. This preliminary action provides an initial focus position estimate, avoiding the need for exhaustive lens sweeps and significantly reducing acquisition time while maintaining focus accuracy.
Solution Approach 2:
The patent replaces the mechanical lens sweeping process with a computational approach using face detection algorithms and distance estimation. Instead of mechanically moving the lens through multiple positions to find focus, the system uses image processing to calculate the optimal focus position directly, substituting mechanical search with intelligent computation.
2Loss of time
If face detection autofocus is used to quickly achieve focus, then acquisition time is reduced, but reliability decreases in low-light conditions or when distinct features are absent
Solution Approach 1:
The system implements feedback by continuously monitoring face detection stability across multiple frames. When face detection becomes unstable or fails (indicating low-light conditions or absent features), the system detects this through feedback loops and switches to alternative focus determination methods, ensuring reliable focus achievement regardless of lighting conditions or subject features.
Solution Approach 2:
The patent creates a multi-functional autofocus system that can operate in multiple modes: face detection mode for quick focusing when faces are present, and alternative methods (such as contrast detection or distance-based focusing) when face detection is unreliable. This universal approach ensures the system can achieve focus reliably across diverse conditions while maintaining speed when possible.
3Measurement precision
If lens sweeps are performed frequently to maintain focus, then focus accuracy is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary face detection and distance estimation to predict the optimal focus position before actual image capture. This preliminary action allows the system to adjust the lens directly to the predicted position without performing energy-consuming lens sweeps, significantly reducing energy consumption while maintaining focus accuracy.
Solution Approach 2:
The system uses the detected face information and estimated distance to self-determine the optimal focus position without requiring external verification through lens sweeps. The face detection and distance estimation mechanisms serve the dual purpose of both subject identification and focus determination, eliminating redundant energy-consuming operations.
Data Source
AI summary
A method for acquiring an image comprises acquiring a first image frame including a region containing a subject at a first focus position; determining a first sharpness of the subject within the first image frame; identifying an imaged subject size within the first image frame; determining a second focus position based on the imaged subject size; acquiring a second image frame at the second focus position; and determining a second sharpness of the subject within the second image frame. A sharpness threshold is determined as a function of image acquisition parameters for the first and/or second image frame. Responsive to the second sharpness not exceeding the first sharpness and the sharpness threshold, camera motion parameters and/or subject motion parameters for the second image frame are determined before performing a focus sweep to determine an optimal focus position for the subject.