How Computers Automatically Organize and Search Photos Using Contextual Data
A system for indexing images by attaching descriptive data to objects within them and adjusting search rankings based on how often a user searches for those specific items.
Original patent title: “System and method of organizing images”
A system for indexing images by attaching descriptive data to objects within them and adjusting search rankings based on how often a user searches for those specific items. Granted to AT&T Intellectual Property I LP in 2014 with 22 claims and 2 forward citations.
Key facts
Coverage
What does this patent actually cover?
This patent describes a method for making photo libraries smarter by attaching 'scene description information'—such as audio, device orientation, or object detection data—to images. It creates a data structure where each object identified in a photo is assigned a weight, which determines how relevant that object is to a search. Crucially, the system tracks a user's search habits and updates these weights over time. For example, if you frequently search for 'dog,' the system increases the weight of 'dog' objects in your photos, making them appear higher in search results.
The gap
What does this patent NOT cover?
- Does not cover simple image tagging based solely on manual user input.
- Does not cover geographic-based image sorting, as the claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more → explicitly state the weights are independent of location.
- Does not cover basic image retrieval that lacks the specific 'infinite array' data structure for object weights.
- Does not cover image processing that does not incorporate user search history to modify object weights.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
What made this novel
The system uses an 'infinite array' to store weights for objects, allowing the database to dynamically adjust the importance of specific items (like a dog or a car) based on the user's personal search history rather than just generic metadata.
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
Google Photos search functionality
Apple Photos object recognition and search
Smart home security camera indexing
Why it matters
The bigger picture
This patent represents an early effort to move beyond simple file-name searching toward semantic, context-aware image retrieval. It highlights the shift from static databases to systems that learn from user behavior to improve relevance, a core component of modern digital photo management.
Filed
November 15, 2007
Granted
October 14, 2014
Market context
Who's building on this
Companies in this space
Major tech companies like Google, Apple, and Amazon are the primary builders in this space, having integrated sophisticated object recognition and personalized search ranking into their respective cloud-based photo services.
Market impact
This patent reflects the industry-wide transition toward 'intelligent' media management. It helped frame the expectation that photo libraries should be searchable by content rather than just date or filename, influencing the development of modern AI-driven media organization tools.
Claim 1 — Plain English
What this patent covers
This patent describes a method for making photo libraries smarter by attaching 'scene description information'—such as audio, device orientation, or object detection data—to images. It creates a data structure where each object identified in a photo is assigned a weight, which determines how relevant that object is to a search. Crucially, the system tracks a user's search habits and updates these weights over time. For example, if you frequently search for 'dog,' the system increases the weight of 'dog' objects in your photos, making them appear higher in search results.
The clever bit
The system uses an 'infinite array' to store weights for objects, allowing the database to dynamically adjust the importance of specific items (like a dog or a car) based on the user's personal search history rather than just generic metadata.
What it does not cover
- Does not cover simple image tagging based solely on manual user input.
- Does not cover geographic-based image sorting, as the claims explicitly state the weights are independent of location.
- Does not cover basic image retrieval that lacks the specific 'infinite array' data structure for object weights.
- Does not cover image processing that does not incorporate user search history to modify object weights.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
PatentBrief Score
Impact Score
Moderate
Citation count
10/40
Early citations
Claim breadth
15/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
5/20
Granted 10–20 years ago
Assignee scale
20/20
Major company or institution
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
$31K – $100K
Midpoint $62K · 1.4 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.
The original legal language
Original claims
22 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Blewett, C., Vesonder, G. T., Bocchieri, E., Killian, T., Kirk, T., Fabbrizio, G. D., Kormann, D., & Henderson, D. (2014). How Computers Automatically Organize and Search Photos Using Contextual Data (U.S. Patent No. 8,862,582). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/8862582/amazon-redshift
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Computers Automatically Organize and Search Photos Using Contextual Data cover?
A system for indexing images by attaching descriptive data to objects within them and adjusting search rankings based on how often a user searches for those specific items.
Who owns patent US 8862582?
AT&T Intellectual Property I LP owns this patent, granted in 2014.
When does this patent expire?
This patent is expected to expire on October 14, 2034, when the invention enters the public domain.
What is patent US 8862582 cited by?
This patent has been cited by 2 later patents that build on its ideas.
What problem does this patent solve?
This patent represents an early effort to move beyond simple file-name searching toward semantic, context-aware image retrieval. It highlights the shift from static databases to systems that learn from user behavior to improve relevance, a core component of modern digital photo management.
What does this patent NOT cover?
Does not cover simple image tagging based solely on manual user input.
Same assignee
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