Camera Array Autofocus via Range Segmentation and Curve Synthesis
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Solution Overview
Problem
Existing autofocus systems face challenges in accurately focusing on subjects with transparent objects in the way and struggle with distant subjects due to limitations in ultrasonic or infrared wave range, and passive contrast detection schemes require complex calculations for optimal focus determination.
Innovation Solution
A camera array system with multiple cameras and a control circuit that divides the autofocus range, scans each portion, estimates focus value curves, and converts them into a camera-independent focus value curve using a correction function for rapid and accurate autofocus, allowing for overlapping fields of view and different exposure settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single camera performs autofocus by scanning the entire autofocus range, then focus accuracy is achieved, but autofocus speed is slow
Solution Approach 1:
The autofocus range is divided into multiple sub-ranges, with each camera in the array responsible for scanning a specific portion. This segmentation allows parallel processing of focus detection across different distance zones, significantly reducing the time required to complete autofocus while maintaining accurate focus determination through aggregation of results from all cameras.
2Productivity
If multiple cameras are used to improve autofocus speed, then scanning speed increases, but system complexity increases
Solution Approach 1:
Multiple cameras are combined into a unified camera array system with coordinated control. The control circuit integrates focus value curves from all cameras and synthesizes a comprehensive focus determination, achieving rapid autofocus through parallel operation while managing system complexity through centralized coordination and data fusion.
Solution Approach 2:
The system transitions from a single-camera sequential scanning approach to a multi-camera parallel scanning architecture, adding the spatial dimension of multiple simultaneous scanning operations. This dimensional change enables concurrent focus detection across different autofocus range portions, dramatically improving speed without proportionally increasing control complexity.
3Reliability
If passive contrast detection scheme is used, then focus on transparent objects is improved, but calculation complexity increases
Solution Approach 1:
The control circuit serves as an intermediary that aggregates focus value curves from multiple cameras and synthesizes the final focus determination. This intermediary processing layer simplifies the calculation complexity by systematically combining contrast detection results from multiple cameras, enabling reliable focus on transparent objects through coordinated multi-camera observation rather than complex single-camera calculations.
Data Source
AI summary
Provided is an imaging system and a method of autofocusing the same. The imaging system includes a camera array including a plurality of cameras to image an image, and a control circuit to control the plurality of cameras to autofocus, and to output a single image by combining images output from the plurality of cameras.