How Cameras Automatically Re-Adjust Themselves Using Fixed Objects
This patent describes a method for surveillance cameras to automatically correct their aim and focus by comparing what they currently see to old calibration images, specifically looking for fixed objects in the scene.
Original patent title: “Automated recalibration of sensors for monitoring an area of real space”
This patent describes a method for surveillance cameras to automatically correct their aim and focus by comparing what they currently see to old calibration images, specifically looking for fixed objects in the scene. Granted in 2026.
Coverage
What does this patent actually cover?
The patent outlines an automated system for recalibrating cameras that monitor a real-world area. It works by taking new images and comparing them to a set of older, known-good calibration images. A special computer program, called a trained neural network classifier, finds specific points on 'relatively immobile structures' (like walls or furniture) in both the new and old images. If the way these points have shifted, called 'transformation information,' reaches a certain level, the camera's settings are automatically updated to correct its view. For example, if a security camera slightly shifts due to vibration, this system would detect the shift by comparing a new image of a doorway to the original calibrated image of that same doorway, then automatically adjust the camera's internal settings to restore its proper alignment.
The gap
What does this patent NOT cover?
- Does not cover manual recalibration where a human physically adjusts the camera or its settings.
- Does not cover recalibration methods that rely on moving objects or people in the monitored area.
- Does not cover systems that recalibrate without using a trained neural network classifier to identify features.
- Does not cover recalibration that does not compare current images to a previously stored set of calibration images.
- Does not cover recalibration based on changes in lighting or color, focusing instead on structural features.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The clever part is using a trained neural network to specifically identify and track features on 'relatively immobile structures' within an area. This allows the system to accurately detect camera drift and automatically correct it, without needing special markers or human input.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Smart home security cameras
Industrial monitoring systems
Robotics vision systems
Traffic monitoring cameras
Augmented reality applications that map real spaces
Why it matters
The bigger picture
Automated recalibration is important for any system relying on consistent camera views, such as security, robotics, or industrial monitoring. It reduces the need for human intervention, saving time and labor costs. This technology helps ensure that cameras remain accurate over long periods, even if they experience minor shifts or disturbances.
Filed
August 22, 2024
Granted
September 15, 2026
Market context
Who's building on this
Companies in this space
Companies developing advanced surveillance and smart home technologies, such as Arlo, Ring, and Google Nest, are actively working on improving camera reliability and autonomy. Manufacturers of industrial automation and robotics, like Boston Dynamics and ABB, also integrate similar self-correction capabilities into their vision systems. Major cloud providers offering video analytics services also benefit from such foundational technologies.
Market impact
This type of automated recalibration technology significantly enhances the reliability and reduces the operational costs of camera-based monitoring systems across various industries. It enables continuous, accurate data collection without frequent human intervention, which is crucial for scaling deployments in security, smart cities, and industrial automation. This capability helps make camera systems more robust and practical for long-term, unattended operation, fostering broader adoption of vision-based solutions.
Claim 1 — Plain English
What this patent covers
The patent outlines an automated system for recalibrating cameras that monitor a real-world area. It works by taking new images and comparing them to a set of older, known-good calibration images. A special computer program, called a trained neural network classifier, finds specific points on 'relatively immobile structures' (like walls or furniture) in both the new and old images. If the way these points have shifted, called 'transformation information,' reaches a certain level, the camera's settings are automatically updated to correct its view. For example, if a security camera slightly shifts due to vibration, this system would detect the shift by comparing a new image of a doorway to the original calibrated image of that same doorway, then automatically adjust the camera's internal settings to restore its proper alignment.
The clever bit
The clever part is using a trained neural network to specifically identify and track features on 'relatively immobile structures' within an area. This allows the system to accurately detect camera drift and automatically correct it, without needing special markers or human input.
What it does not cover
- Does not cover manual recalibration where a human physically adjusts the camera or its settings.
- Does not cover recalibration methods that rely on moving objects or people in the monitored area.
- Does not cover systems that recalibrate without using a trained neural network classifier to identify features.
- Does not cover recalibration that does not compare current images to a previously stored set of calibration images.
- Does not cover recalibration based on changes in lighting or color, focusing instead on structural features.
Patent timeline
Application submitted to the patent office
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
0/20
Narrow claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$19K – $61K
Midpoint $38K · 17.9 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
Concepts involved
Cite this patent
(2026). How Cameras Automatically Re-Adjust Themselves Using Fixed Objects (U.S. Patent No. 12,737,921). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12737921/automated-recalibration-of-sensors-for-monitoring-an-area-of-real-space
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
Embed
Add this patent to your site
Drop this plain-English patent card into any blog post or article — free, no signup. It always links back to the full breakdown here.
<div data-patentlens-widget data-patent-number="US12737921"></div> <script src="https://patentbrief.org/embed.js" async></script>
Stay in the loop
Get a weekly digest of new patents.
One email per week. No spam. Unsubscribe anytime.
Keep exploring
Related patents you should know
US 4683195 · 1987
How to Make Billions of Copies of a DNA Segment
This patent describes the Polymerase Chain Reaction (PCR), a method to rapidly create many copies of a specific piece of DNA or RNA, enabling its detection and analysis.
Cetus Corp
US 8697359 · 2014
How to Edit Genes in Human Cells Using an Engineered CRISPR System
This patent describes an engineered CRISPR-Cas9 system for precisely cutting DNA in eukaryotic cells to change how genes work, opening the door for gene editing in complex organisms.
Massachusetts Institute of Technology
US 7657849 · 2010
How the iPhone's Slide-to-Unlock Gesture Works
Apple's 2010 patent describes unlocking a device by dragging a specific graphical image across the touchscreen along a predefined path, a gesture that became iconic with the original iPhone.
Apple Inc
US 4733665 · 1988
How Doctors Implant a Permanent Stent Using a Balloon
This patent describes the method for placing a permanent, expandable wire mesh tube inside a blood vessel or other body tube using a balloon-tipped catheter to widen it and keep it open.
Expandable Grafts Partnership
US 4965188 · 1990
How to Make Many Copies of a DNA Piece with Heat
This patent describes the Polymerase Chain Reaction (PCR) method, a technique to make millions of copies of a specific DNA segment using a heat-resistant enzyme and repeated temperature changes.
Cetus Corp
US 4235871 · 1980
How to Encapsulate Active Materials in Lipid Bubbles Efficiently
This patent describes a method for trapping biologically active substances inside tiny, multi-layered fat bubbles called liposomes, using a specific water-in-oil emulsion and gel-forming process to improve how much material gets captured.
Individual
More to explore
More in Consumer Electronics
US 7657849 · 2010 · Apple Inc
How the iPhone's Slide-to-Unlock Gesture Works
US 7479949 · 2009 · Apple Inc
How Touchscreens Understand Your Finger Swipes and Scrolls
US 4528643 · 1985 · FPDC Inc
How Stores Make Custom Products On-Demand with Remote Approval
US 7469381 · 2008 · Apple Inc
How Touchscreens Show and Snap Back When You Scroll Past an Edge
New to patents?
Common Questions
Frequently Asked Questions
What does How Cameras Automatically Re-Adjust Themselves Using Fixed Objects cover?
This patent describes a method for surveillance cameras to automatically correct their aim and focus by comparing what they currently see to old calibration images, specifically looking for fixed objects in the scene.
When does this patent expire?
This patent is expected to expire on September 15, 2046, when the invention enters the public domain.
What problem does this patent solve?
Automated recalibration is important for any system relying on consistent camera views, such as security, robotics, or industrial monitoring. It reduces the need for human intervention, saving time and labor costs. This technology helps ensure that cameras remain accurate over long periods, even if they experience minor shifts or disturbances.
What does this patent NOT cover?
Does not cover manual recalibration where a human physically adjusts the camera or its settings.
Patent monitoring