Focus Tracking Control Using Shield Detection in Framed Scenes
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Solution Overview
Problem
Existing focus control systems struggle with accurate focus tracking determination, particularly when obstacles or changes in framing occur, leading to incorrect focus adjustments on unintended objects.
Innovation Solution
A focus control apparatus and method that utilizes a Convolutional Neural Network (CNN) to detect and differentiate between main objects and potential obstacles or shields, incorporating shield information to refine focus tracking decisions based on object recognition and predicted image plane positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If focus tracking determination is made based only on detected defocus amount, then focus control is simple, but focus tracking accuracy deteriorates when obstacles or framing changes occur
Solution Approach 1:
The patent segments the focus determination process into multiple independent components: defocus amount detection, shield area detection, and focus tracking determination. By separating these functions and requiring multiple conditions to be satisfied simultaneously, the system achieves more accurate focus tracking without excessive complexity in any single component.
Solution Approach 2:
The patent adds a new dimension to focus determination by introducing shield area detection as an additional criterion alongside defocus amount measurement. This dimensional expansion allows the system to distinguish between legitimate focus targets and obstacles, improving accuracy without fundamentally changing the existing focus control mechanism.
2Speed
If focus tracking is performed on obstacles with small defocus amounts, then focus control is responsive, but focus tracking reliability deteriorates due to unintended focus on wrong objects
Solution Approach 1:
The patent introduces shield area detection as an intermediary mechanism that mediates between the defocus amount measurement and the final focus tracking decision. This intermediary component filters out false positives by identifying obstacles that should not trigger focus tracking, thereby maintaining reliability while preserving response speed.
Solution Approach 2:
The system implements feedback by continuously monitoring both defocus amount and shield area information, using this feedback to dynamically adjust focus tracking decisions. When shield information indicates an obstacle, the system suppresses focus tracking even if defocus amount suggests otherwise, ensuring reliable focus on intended subjects.
3Productivity
If focus tracking determination uses only defocus amount threshold, then processing is fast, but measurement precision deteriorates in complex scenes with multiple objects
Solution Approach 1:
The patent segments the processing into parallel operations: defocus amount calculation and shield area detection can proceed simultaneously without sequential dependency. This segmentation maintains processing speed while adding the precision benefit of multi-criteria evaluation, as both computations occur independently before being integrated for final decision-making.
Data Source
AI summary
An apparatus configured to perform focus tracking on an object within a detection area to detect a defocus amount within an imaging angle of view includes a memory storing instructions, and a processor configured to execute the instructions to perform focus tracking determination to determine whether or not the focus tracking is to be performed using information about the defocus amount, and acquire information about a shield against the object from image data generated by imaging. The processor is configured to perform the focus tracking determination using information about the shield acquired in the detection area.