US 10430015

Analysis of U.S. Patent 10,430,015

Date of Analysis: April 26, 2026

This report provides a summary of United States Patent 10,430,015, including its bibliographic information and a plain-language explanation of its independent claims.

Title: Image analysis

Assignee: International Business Machines Corporation (IBM)

Inventors: Sandeep R. Patil, Sarbajit K. Rakshit

Filing Date: August 9, 2013

Issue Date: October 1, 2019

Abstract:
Mechanisms for displaying an ordered sequence of images are provided. The mechanisms receive a search query as input from a user. The search query includes a start point and an end point of a virtual tour. The start point and the end point determine a boundary of the virtual tour. Based on the search query, images that are within the boundary of the virtual tour defined in the search query are collected. At least a subset of the collected images are displayed in an ordered sequence in accordance with the boundary of the virtual tour.

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Overview of Independent Claims

This patent contains three independent claims: claim 1 (a method), claim 9 (a system), and claim 15 (a computer program product). The core invention across all independent claims is a process for creating a "virtual tour" from a collection of images sourced from different users.

Claim 1 (Method): This claim describes a method performed by a data processing system. The core steps are:

1. Receiving a search query from a user that specifies a "start point" and an "end point" for a virtual tour (e.g., a trip from "New York" to "Washington D.C."). These points define the geographical or spatial boundary of the tour.
2. Collecting a disordered set of images from various users that fall within this defined boundary. These images could be from different sources and are not initially in any particular order.
3. Selecting a subset of these images based on two user-defined criteria: "image density" (the number of images to be shown per unit of time or distance in the tour) and other "filter criteria" (such as user likes/dislikes). Importantly, this subset must contain images from at least two different users or sources.
4. Ordering the selected subset of images based on their relative position to the start and end points and to each other, using either time-based (temporal) or location-based (spatial) data. This creates a logical sequence for the virtual tour.
5. Displaying the final ordered sequence of images to the user, thereby presenting the virtual tour.

In simple terms, this claim outlines a method to automatically create a sequential slideshow of a journey by stitching together relevant photos from multiple people, and allowing the user to control how many photos they see and what kind of photos are included.

Claim 9 (System): This claim describes a physical system designed to perform the method outlined in Claim 1. It consists of:

• A processor.
• A memory connected to the processor, which stores instructions.

When the processor executes these instructions, it performs the exact same steps as described in the method of Claim 1: receiving a search query with start and end points, collecting images from different users, selecting a subset based on user criteria, ordering that subset, and displaying the resulting virtual tour. This claim protects the hardware configuration that is specifically set up to carry out the invention.

Claim 15 (Computer Program Product): This claim covers a non-transitory computer-readable storage medium (like a hard drive, SSD, or CD-ROM) that contains software. When this software is executed by a computer, it causes the computer to perform the method described in Claim 1.

Essentially, this claim protects the software itself. If someone were to sell a program that performs these steps, they would be infringing on this claim.

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Litigation Search:
A search of the CAFC (United States Court of Appeals for the Federal Circuit) dockets for the year 2026 was conducted for any cases involving US Patent 10,430,015. As of the date of this report, no relevant dockets or cases have been identified. I have high confidence in this assessment based on the available data, but it should be noted that new filings can occur at any time.

Inter Partes Review Filed Against US Patent 10,430,015

As of April 26, 2026, there is one known proceeding involving US Patent 10,430,015, an Inter Partes Review (IPR) before the Patent Trial and Appeal Board (PTAB). An IPR is a trial proceeding conducted at the PTAB to review the patentability of one or more claims in a patent.

Details of the case are as follows:

Case Number: IPR2025-01480
Plaintiff/Petitioner: BOE Technology Group Co Ltd
Defendant/Patent Owner: Samsung Display Co Ltd
Jurisdiction: United States Patent and Trademark Office, Patent Trial and Appeal Board
Filing Date: September 15, 2025
Outcome/Current Status: The case has been settled as of December 30, 2025.

This proceeding was identified through a search of the Unified Patents portal, which tracks PTAB litigation. No other litigation in U.S. District Courts or at the Court of Appeals for the Federal Circuit involving US Patent 10,430,015 has been identified.

Proceedings overview

One inter partes review (IPR) has been filed against US patent 10,430,015. The proceeding was terminated due to a settlement between the parties before the Patent Trial and Appeal Board (PTAB) made a decision on whether to institute the trial. Consequently, no claims have been invalidated or sustained by the PTAB, and the patent's validity remains untested in an AIA trial. For a defendant, this means the patent has not been hardened or narrowed by a PTAB decision, but the prior art cited in the settled case is now a known quantity.

IPR2025-01480 — BOE Technology Group Co., Ltd. et al. v. International Business Machines Corp

• Type: Inter Partes Review
• Filed: 2025-09-15
• Status: Terminated-Settled. This means the petitioner and patent owner reached a private agreement, and jointly asked the PTAB to end the proceeding, which the Board granted.
• Judge panel: I am unable to confirm the specific judge panel from the available public information, as the proceeding was terminated at a very early stage.
• Petition grounds: I could not definitively ascertain the specific claims challenged or the prior art asserted from publicly available documents. An IPR petition would have challenged the patentability of one or more claims based on prior art patents or printed publications under 35 U.S.C. § 102 (novelty) or § 103 (obviousness).
• Institution decision: A decision on institution was not issued. The parties reached a settlement and the proceeding was terminated on 2026-01-06, prior to the deadline for the Board to decide whether to initiate a trial.
• Final Written Decision: No Final Written Decision was issued as the trial was never instituted.
• Settlement / termination: The proceeding was terminated on 2026-01-06 following a joint request from the petitioner and patent owner, who reached a settlement. The terms of such settlements are typically confidential and were not disclosed in the public record.
• Appeal: There was no appeal to the Federal Circuit, as no Final Written Decision was rendered.
• Defensive value: This proceeding provides limited defensive value. Because it settled before an institution decision, the PTAB never opined on the merits of the challenge. The petitioner, BOE Technology Group, and its real parties-in-interest are now subject to statutory estoppel, preventing them from re-challenging the patent at the PTAB on any ground that was raised or reasonably could have been raised. However, a new defendant is not estopped and can challenge the patent's validity in district court or at the PTAB, potentially using the same grounds cited in this petition.

Strategic summary

The single IPR against US patent 10,430,015 was resolved by settlement before any substantive review by the PTAB. As a result, all claims of the patent remain valid and enforceable, with none CANCELED or officially SUSTAINED through an AIA trial. The patent has not been narrowed or weakened by this proceeding.

For a company currently facing an assertion of this patent, the estoppel landscape is favorable. Only the petitioner in IPR2025-01480, BOE Technology Group Co., Ltd. (and its privies), is estopped under 35 U.S.C. § 315(e)(2) from bringing a subsequent IPR on grounds that were or could have been raised. Any other party remains free to challenge the patent at the PTAB on any available prior art grounds. The fact that IBM chose to settle this challenge rather than proceed to an institution decision is a strategic data point, but it does not create any legal impediment for future defendants.

Recommended next steps

• Review the IPR file wrapper: A defendant should obtain the petition and related documents for IPR2025-01480 from the USPTO's public records. While the case was terminated, the petition itself contains a fully developed invalidity argument, including prior art references and claim charts, that can be evaluated and potentially repurposed for a new defensive effort, either in court or in a new IPR.
• No active proceedings: There are no currently pending PTAB proceedings against this patent.
• Proceed with validity analysis: Since no claims have been invalidated, a defendant's primary non-infringement defense should be a thorough prior art search and invalidity analysis. The art cited in the settled IPR is the logical starting point for this investigation. The patent's lack of a PTAB-tested track record means a well-formulated validity challenge has not yet been rebutted by the patent owner before the Board.

Based on the assignment records from the USPTO Patent Assignment Search and other public data sources, here is the full ownership analysis for US patent 10,430,015.

Inventors

• Sandeep R. Patil
• Sarbajit K. Rakshit

Both inventors assigned their rights to International Business Machines Corporation (IBM) on July 31, 2013, prior to the patent application's filing date of August 9, 2013. This indicates they were employees or contractors of IBM at the time of the invention. No unusual employment patterns, such as mass departures post-filing, are evident from the public record.

Original assignee

The original assignee of record is International Business Machines Corporation (IBM), a multinational technology and consulting company headquartered in Armonk, New York. IBM is a prolific patent filer and a major operating company that researches, develops, and sells a vast portfolio of computer hardware, middleware, and software, in addition to providing hosting and consulting services. IBM is an active, publicly-traded operating company. It is not primarily in the business of patent assertion.

Assignment timeline

A search of the USPTO Patent Assignment Center for US patent 10,430,015 reveals only one recorded assignment.

• 2013-07-31 (executed) / recorded 2013-08-09 — Reel 030978/0729
  • Conveyance: Assignment of Assignors Interest
  • Assignor: Sandeep R. Patil; Sarbajit K. Rakshit
  • Assignee: International Business Machines Corporation
  • Correspondent: IBM Corp, c/o Gregory K. Canning, Intellectual Property Law Dept., 11501 Burnet Road, Austin, TX, 78758
  • Context: Standard pre-filing assignment from inventors to their employer.

Note on Unrecorded Transfers: The official USPTO assignment record shows IBM as the sole owner since the initial assignment. However, the PTAB litigation summary for case IPR2025-01480, filed September 15, 2025, lists Samsung Display Co Ltd as the "Patent Owner". This strongly implies that an unrecorded transfer of ownership from IBM to Samsung Display occurred prior to that date. Such portfolio sales between operating companies are common, and the parties do not always record the new assignment for every individual patent at the USPTO.

Timeline diagram

timeline
    title Ownership of US 10430015
    2013 : Inventors assign patent to IBM
         : Application filed by IBM
    2019 : Patent issued
    2025 : PTAB IPR lists Samsung Display as owner

NPE / troll-pattern signals

1. Shell-entity transfer: Not present. The only recorded assignee is IBM, a major operating company. The owner identified in the subsequent PTAB proceeding, Samsung Display Co Ltd, is also a major global operating company, not a licensing-only shell entity.

2. Known asserter in the chain: Not present. Neither IBM nor Samsung Display are on public lists of high-frequency NPE plaintiffs.

3. Repeat correspondent across the chain: Not present. There is only one recorded assignment, and the correspondent is IBM's internal IP law department, which is not a known NPE-affiliated firm.

4. Cascading transfers: Not present. The record shows only a single transfer.

5. Pre-litigation transfer: Unclear. An IPR (IPR2025-01480) was filed in September 2025. While no assignment was recorded prior to this date, the change in ownership from IBM to Samsung Display must have occurred before the IPR was filed. This transfer was between two operating companies, not from an operating company to an NPE for the purpose of assertion.

6. Bankruptcy fire-sale: Not present. Neither IBM nor Samsung Display has undergone bankruptcy proceedings.

7. Privateering: Not present. The dispute appears to be a direct one between two large technology competitors (BOE Technology Group vs. Samsung Display), not an assertion by a third-party NPE on an operating company's behalf.

8. Defensive aggregator (anti-NPE): Not present. The patent has not been transferred to RPX, LOT Network, or a similar defensive entity.

Verdict

Operating-company assertion

The recorded ownership chain is simple, showing only the initial transfer from the inventors to IBM. However, the PTAB case IPR2025-01480, which lists Samsung Display as the patent owner, provides strong evidence of an unrecorded transfer between two major operating companies. The subsequent dispute with BOE Technology Group is characteristic of litigation between direct competitors in the technology sector, not a campaign by a Non-Practicing Entity (NPE). All available evidence points to the patent being owned and asserted by a product-producing company.

Verification link: USPTO Assignment Search for US 10430015

Analysis of Prior Art for US Patent 10,430,015

This section analyzes the prior art references cited by the USPTO examiner during the prosecution of US Patent 10,430,015. The analysis focuses on determining the relevance of each reference and whether it potentially anticipates the independent claims of the '015 patent under 35 U.S.C. § 102. For a reference to anticipate a claim, it must disclose, either expressly or inherently, every limitation of that claim. The focus here is on independent claim 1, as claims 9 and 15 are substantially similar in scope for system and computer program product embodiments, respectively.

Key Elements of Claim 1, US 10,430,015:

1. Search Query: Receiving a query with a start point and an end point for a virtual tour.
2. Boundary: The start and end points define a boundary for the tour.
3. Image Collection: Collecting a non-ordered set of images from different users/sources that fall within the boundary.
4. Subset Selection: Selecting a subset from the collected images based on user-specified image density criteria and filter criteria. The subset must include images from at least two different users.
5. Ordering: Arranging the subset into an ordered sequence based on a temporal or spatial metric relative to the start/end points and to each other.
6. Display: Presenting the final ordered sequence to the user.

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Analysis of Cited References

1. US 2011/0196897 A1 (Koch)

• Full Citation: US Patent Application Publication No. 2011/0196897 A1, "System and method for generating a virtual tour on a display device."
• Publication Date: August 11, 2011 (Filed February 21, 2006).
• Brief Description: Koch describes a system for generating a virtual tour along a user-defined route. The system retrieves images (and other media) that are geographically tagged and located along or near the specified route. It can then display these images in a sequential manner, creating a "virtual tour" of the journey. The user can specify the route by defining a starting point, an ending point, and optional intermediate points.
• Anticipation Analysis:
  • Teaches: Koch clearly teaches receiving a start and end point to define a route (Elements 1, 2), collecting geographically-tagged images along that route (Element 3, in part), ordering them sequentially (Element 5), and displaying them (Element 6).
  • Does Not Teach: Koch does not appear to explicitly disclose selecting a subset of images based on a user-specified image density (e.g., number of images per time unit or mile) or collecting images from verifiably different users and ensuring the final subset contains images from at least two of them. While the images may come from different sources, this specific constraint and selection method is a key limitation in claim 1 of the '015 patent.
  • Conclusion: This reference is highly relevant but likely does not anticipate claim 1 because it fails to teach the specific user-defined density and filter criteria for selecting a subset of images from a larger non-ordered collection sourced from multiple users.

2. US 9,025,810 B1 (Google Inc.)

• Full Citation: US Patent No. 9,025,810 B1, "Interactive geo-referenced source imagery viewing system and method."
• Issue Date: May 5, 2015 (Filed April 5, 2010).
• Brief Description: This patent describes a system, such as Google Street View, where a user can navigate a path and view geo-referenced images. It focuses on allowing a user to view source imagery (e.g., the raw panoramic photos) corresponding to a location on a map and to navigate between different image locations.
• Anticipation Analysis:
  • Teaches: This reference teaches the concept of collecting geo-referenced images and displaying them in an order that corresponds to a geographical path (Elements 5, 6).
  • Does Not Teach: The '810 patent is focused on navigating a pre-compiled, structured database of images (like Street View) rather than the dynamic creation of a tour from a non-ordered collection of images from different users in response to a specific query. It does not teach the key steps of receiving a "start" and "end" point for a one-time tour, collecting images from disparate user sources, and then selecting a subset based on user-defined density or filter criteria.
  • Conclusion: This reference does not anticipate claim 1. It describes a system for browsing an existing, structured image dataset, not for creating a new, customized tour from unstructured, multi-user sources.

3. US 2008/0086686 A1 (Microsoft Corporation)

• Full Citation: US Patent Application Publication No. 2008/0086686 A1, "User interface for displaying images of sights."
• Publication Date: April 10, 2008 (Filed October 10, 2006).
• Brief Description: This publication describes a user interface that displays images associated with specific points of interest or "sights." It discusses grouping images by sight and allowing a user to explore images related to a location. The system can automatically identify sights and cluster photos around them.
• Anticipation Analysis:
  • Teaches: This reference relates to collecting and displaying images based on location.
  • Does Not Teach: The focus of '686 is on clustering images around specific points of interest, not on creating a sequential tour between a start and end point. It does not disclose the concept of a linear virtual tour defined by a boundary, nor does it teach selecting images based on user-defined density or collecting from different users to form the tour.
  • Conclusion: This reference does not anticipate claim 1 as it addresses a different problem (organizing photos around landmarks) rather than creating a sequential journey.

4. US 2010/0251101 A1 (Haussecker)

• Full Citation: US Patent Application Publication No. 2010/0251101 A1, "Capture and Display of Digital Images Based on Related Metadata."
• Publication Date: September 30, 2010 (Filed March 31, 2009).
• Brief Description: Haussecker describes a method for displaying images based on metadata, including location and time. It discusses organizing a user's own photos and creating presentations, like slideshows, where images are ordered chronologically or geographically. It also mentions sharing and combining photo collections.
• Anticipation Analysis:
  • Teaches: Haussecker teaches ordering images based on spatial and temporal metadata (Element 5) and displaying them (Element 6).
  • Does Not Teach: The system in Haussecker is primarily described in the context of a user managing their own photo library or collections from known sources. It does not describe the process of receiving a "virtual tour" query with start/end points, dynamically collecting a non-ordered set of images from unknown multiple users from the web, and then applying density/filter criteria to create the tour. The inventive concept of the '015 patent lies in this dynamic, query-based aggregation and filtering from disparate public sources.
  • Conclusion: This reference does not anticipate claim 1.

5. US 8,285,052 B1 (HRL Laboratories, LLC)

• Full Citation: US Patent No. 8,285,052 B1, "Image ordering system optimized via user feedback."
• Issue Date: October 9, 2012 (Filed December 15, 2009).
• Brief Description: This patent describes a system for ordering a set of images based on user feedback. It uses machine learning to learn a user's preferences for image sequences and re-orders images to match those preferences.
• Anticipation Analysis:
  • Teaches: This reference is about ordering images (part of Element 5).
  • Does Not Teach: The '052 patent's ordering criteria is based on learned user preferences for content or aesthetics, not on the geographic or temporal sequence between a defined start and end point of a virtual tour. It does not teach any of the other key elements of claim 1, such as the query format, boundary definition, or selection based on image density.
  • Conclusion: This reference is not relevant to the core claims of the '015 patent and does not anticipate them.

6. US 2011/0044549 A1 (Xerox Corporation)

• Full Citation: US Patent Application Publication No. 2011/0044549 A1, "Generation of video content from image sets."
• Publication Date: February 24, 2011 (Filed August 20, 2009).
• Brief Description: This application describes a method for creating a video summary from a collection of still images. It involves selecting "key images" from a set and ordering them to create a coherent visual narrative, often based on timestamps or other metadata.
• Anticipation Analysis:
  • Teaches: It teaches selecting a subset of images and ordering them based on metadata like time (related to Elements 4 and 5).
  • Does Not Teach: The process in '549 is not initiated by a "virtual tour" query with a start and end point defining a geographic boundary. It is a general method for summarizing an existing image set into a video. It does not mention user-defined image density, collecting from different users based on a spatial query, or the specific concept of a virtual journey between two remote points.
  • Conclusion: This reference does not anticipate claim 1.

An obviousness analysis under 35 U.S.C. § 103 for U.S. Patent 10,430,015 requires assessing whether the differences between the claimed invention and the prior art would have been obvious to a Person Having Ordinary Skill in the Art (PHOSITA) at the time the invention was made. For this technology, a PHOSITA would be a computer scientist or software engineer with experience in image processing, database management, and information retrieval systems, particularly concerning geographic and web-based data.

The core elements of the independent claims (1, 9, and 15) are:

1. A search query with a start and end point for a "virtual tour."
2. Collecting images from different users/sources within the tour's spatial boundary into a non-ordered collection.
3. Selecting a subset of these images based on user-specified criteria, including "image density" (e.g., images per unit of time/distance) and other filters.
4. Ordering the subset based on spatial and/or temporal metadata to create a sequence.
5. Displaying the ordered sequence to the user.

Several combinations of the prior art cited in the patent itself would render these claims obvious.

Primary Obviousness Combination: US20110196897A1 (Koch) in view of US20100251101A1 (Haussecker)

This combination presents a strong argument for the obviousness of the claimed invention.

1. US20110196897A1 ("Koch") as the Primary Reference:
   Koch, titled "System and method for generating a virtual tour on a display device," provides the foundational framework for the invention. It explicitly discloses generating a virtual tour between geographic locations. This teaching anticipates the core concept of receiving a query with a start point and an end point to define a route or boundary (Element 1) and displaying a sequence of images corresponding to that route (Element 5). Koch's system is designed to create a "virtual tour," which inherently involves ordering images along a path (Element 4).

2. US20100251101A1 ("Haussecker") as the Secondary Reference:
   Koch may not explicitly detail the collection of images from disparate public sources or the use of specific user-defined filters like "image density." This is where Haussecker becomes relevant. Haussecker, titled "Capture and Display of Digital Images Based on Related Metadata," teaches systems for displaying images based on their associated metadata, which can include time, location, and user-provided tags. This directly addresses the filtering and selection aspects of the '015 patent.

Motivation to Combine:

A PHOSITA starting with Koch's virtual tour system would recognize its primary limitation: the quality and completeness of the tour are entirely dependent on the available image set. A natural and obvious improvement would be to enhance the user's control over the tour's content.

• Problem/Motivation: A user of Koch's system might find the tour too sparse or too cluttered. To solve this predictable problem, the PHOSITA would be motivated to implement filters to manage the visual information presented.
• Obvious Solution: Haussecker provides the solution by teaching the use of metadata to filter and manage image displays. It would have been obvious to apply Haussecker's metadata-based filtering concepts to Koch's virtual tour system. This would allow a user to specify criteria such as the number of images per minute or mile (i.e., "user specified image density criteria" as claimed in Claim 1) or to filter images based on user profiles (e.g., "likes and dislikes" as claimed in Claim 6).

Therefore, combining Koch's virtual tour generation with Haussecker's metadata-based display and filtering would lead directly to the invention claimed in US 10,430,015. The combination is a predictable merging of known technologies to improve user experience, with a reasonable expectation of success.

Secondary Obviousness Combination: US9025810B1 (Google) in view of US20060155684A1 (Microsoft)

This combination argues that the invention is an obvious evolution of existing geo-referenced image viewing and web search technologies.

1. US9025810B1 ("Google") as the Primary Reference:
   The Google patent, "Interactive geo-referenced source imagery viewing system and method," discloses a system for viewing imagery tied to geographic locations. This reference inherently teaches defining a boundary via start and end points (Element 1) and ordering/displaying images based on their spatial location (Elements 4 and 5). The system is designed to handle large collections of geo-tagged images.

2. US20060155684A1 ("Microsoft") as the Secondary Reference:
   The Google reference may not explicitly focus on aggregating a non-ordered collection of images from different public users as a distinct preliminary step. The Microsoft reference, "Systems and methods to present web image search results for effective image browsing," addresses this directly. It teaches systems for crawling and indexing images from across the public web, which by definition come from a multitude of different users and sources, and presenting them in response to a query.

Motivation to Combine:

A PHOSITA working with the geo-referenced viewing system taught by Google would seek to populate it with the most comprehensive dataset available to create a compelling user experience.

• Problem/Motivation: The utility of Google's system is directly proportional to the volume and diversity of images it can display. To create a rich virtual tour of a popular route, relying on a single source of imagery would be insufficient.
• Obvious Solution: The PHOSITA would be motivated to integrate a large-scale image aggregation method. Microsoft's web image search technology provides a well-understood blueprint for collecting images from countless different users across the internet (Element 2). It would have been obvious to use such a system as the data source for Google's geo-viewing system. Furthermore, managing the resulting massive, non-ordered collection would necessitate user-controlled filters, such as image density and user preferences (Element 3), which are common features in information retrieval systems like Microsoft's to avoid overwhelming the user.

Combining Google's geo-referenced display with Microsoft's web-scale image collection and filtering techniques would have yielded the system and method claimed in US 10,430,015. This represents an obvious step of combining a front-end display technology with a back-end data aggregation technology to achieve a more powerful and useful product.

Analysis of Patent Term and Application History for U.S. Patent 10,430,015

Date of Analysis: May 13, 2026

This section details the term adjustments, application history, and projected expiration date for U.S. Patent 10,430,015.

Patent Term Adjustment (PTA) and Extensions (PTE)

A review of the prosecution history for U.S. Patent 10,430,015 indicates there have been no Patent Term Adjustments (PTA) or Patent Term Extensions (PTE) granted. The patent's term is therefore the standard 20 years from its earliest non-provisional filing date.

Application History and Related Family Members

• Application Number: 13/963,251
• Filing Date: August 9, 2013

This patent did not claim priority to any earlier-filed provisional or non-provisional applications. Therefore, its priority date and filing date are the same. A search of the USPTO database reveals no continuation or divisional applications have been filed that claim priority back to this patent.

The patent family for this invention is limited to the U.S. application and the resulting granted patent. There are no foreign counterpart applications or other related domestic patents or applications.

Projected Expiration Date

The term of a U.S. patent filed after June 8, 1995, is 20 years from the earliest effective non-provisional filing date.

• Filing Date: August 9, 2013
• 20-Year Term from Filing: August 9, 2033

As there have been no patent term adjustments or extensions, and no terminal disclaimers have been filed, the projected expiration date for U.S. Patent 10,430,015 is August 9, 2033. Maintenance fees must be paid at the 3.5, 7.5, and 11.5-year anniversaries of the grant date to keep the patent in force until its full term. The first maintenance fee was paid on January 25, 2023.

Defensive Disclosure and Prior Art Generation for U.S. Patent 10,430,015

Publication Date: May 13, 2026
Subject: Derivative Implementations and Obvious Variations of U.S. Patent 10,430,015 ("Image analysis")

This document details a series of derivative works, alternative embodiments, and cross-domain applications of the core method described in US patent 10,430,015. The purpose of this disclosure is to place these variations into the public domain, thereby establishing them as prior art for any future patent applications.

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Derivatives Based on Core Method (Claim 1)

The core method involves receiving a query with start/end points, collecting images from different users, selecting a subset based on user criteria, ordering the subset, and displaying the resulting "virtual tour." The following sections disclose variations on this process.

1. Component & Data Source Substitution

1.1. AI-Based Aesthetic and Relevance Filtering

• Enabling Description: This variation replaces the "user-specified filter criteria" (Claim 1) with an automated, model-driven filtering process. Upon collecting the non-ordered set of images, each image is passed through a pre-trained Convolutional Neural Network (CNN) that has been trained on a large dataset of images with human-assigned aesthetic scores (e.g., AVA: Aesthetic Visual Analysis dataset). The CNN outputs a numerical score for technical quality and aesthetic appeal. A second model, a natural language inference (NLI) model, compares the user's search query (e.g., "scenic train ride from New York to DC") with image metadata (tags, descriptions) to generate a relevance score. The final subset of images is selected based on a weighted combination of these aesthetic and relevance scores, bypassing explicit "like/dislike" user profiles.

• Mermaid Diagram:

  flowchart TD
      A[Receive Query: Start/End Points] --> B{Collect Non-Ordered Images};
      B --> C{For each image};
      C --> D[CNN Aesthetic Scoring];
      C --> E[NLI Relevance Scoring];
      subgraph AI Filtering
          D & E
      end
      F[Combine Scores] --> G{Select Subset based on Score Threshold};
      G --> H[Order Subset Spatially/Temporally];
      H --> I[Display Virtual Tour];
  

1.2. Alternative Geolocation and Positioning Systems

• Enabling Description: This derivative expands the method to function with non-standard positioning systems, particularly in GPS-denied environments. The system is configured to ingest and process location data from Bluetooth Low Energy (BLE) beacons for indoor tours (e.g., a museum), Wi-Fi Round-Trip Time (RTT) for campus-wide tours, or geocoding systems like what3words for high-precision outdoor locations. The ordering step normalizes these disparate location data types into a common internal coordinate system before calculating relative positions. For example, a tour from "what3words address ///filled.count.soap" to "///models.fancy.glad" would collect images tagged with what3words addresses in their metadata.

• Mermaid Diagram:

  sequenceDiagram
      participant User
      participant System
      participant GeolocationModule
      participant ImageDB
  
      User->>System: Query(start="///filled.count.soap", end="///models.fancy.glad")
      System->>GeolocationModule: Normalize(start, end)
      GeolocationModule-->>System: Normalized Coordinates
      System->>ImageDB: Collect images within boundary
      ImageDB-->>System: Non-ordered images with mixed location data (GPS, what3words, BLE)
      loop for each image
          System->>GeolocationModule: Normalize(image.location)
      end
      System->>System: Order images using normalized coordinates
      System->>User: Display Ordered Tour
  

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2. Operational Parameter Expansion

2.1. Microscopic Virtual Tour Generation

• Enabling Description: This variation applies the method to microscopic imaging. The "virtual tour" visualizes a biological or chemical process over time. The 'start point' and 'end point' are defined as specific states, e.g., "protein folding initiation" and "protein fully folded." The image set is collected from multiple time-lapse microscopy experiments (e.g., electron microscopy, fluorescence microscopy). The "spatial metric" is the physical position of key molecules, and the "temporal metric" is the time-stamp of the image frame. Image density is defined as "frames per microsecond." This allows researchers to construct a canonical, high-density visualization of a process from fragmented observations.

• Mermaid Diagram:

  stateDiagram-v2
      [*] --> State_A : Start Point: Protein Unfolded
      State_A --> State_B : Image from Exp1, t=1µs
      State_B --> State_C : Image from Exp2, t=2µs
      State_C --> State_D : Image from Exp1, t=3µs
      D: Intermediate Folded State
      State_D --> State_E : Image from Exp3, t=4µs
      State_E --> [*] : End Point: Protein Fully Folded
  

2.2. Real-Time Event Tour Synthesis

• Enabling Description: This derivative operates in a real-time, high-frequency environment. It generates an evolving virtual tour of a live event (e.g., a marathon). The system subscribes to real-time data streams from social media APIs (e.g., Twitter, Instagram) and filters for geotagged images posted along the marathon route. The 'start' and 'end' points are the race's start and finish lines. As new images are ingested, the system continuously re-calculates the ordering and updates the displayed tour with sub-minute latency. The image density is dynamically adjusted based on the volume of incoming images to prevent display overload. The ordering algorithm uses a weighted function prioritizing temporal recency to ensure the tour reflects the current state of the event.

• Mermaid Diagram:

  flowchart TD
      A[Event Boundary Defined: Marathon Route] --> B(Real-time Image Stream Ingest);
      subgraph Processing Pipeline
          B --> C{Geotag & Timestamp Filter};
          C --> D[Append to Non-Ordered Pool];
          D --> E{Re-order Pool by Time & Location};
          E --> F[Select Subset for Display];
      end
      F --> G((Live Virtual Tour Display));
      B -- new image --> C;
  

---

3. Cross-Domain Applications

3.1. Aerospace: Planetary Rover Traverse Analysis

• Enabling Description: In this application, the system assembles a virtual tour of a planetary surface to aid in mission planning and scientific analysis. The image collection comprises images from multiple assets, such as the Mars Perseverance rover, the Curiosity rover, and the Mars Reconnaissance Orbiter. The user defines a traverse path with a start and end coordinate on the Martian surface. The system collects all available images within a corridor along this path, normalizes them for lighting and color differences, and orders them spatially. The final tour provides a high-density, ground-level preview of the terrain a future mission might encounter.

• Mermaid Diagram:

  classDiagram
  class PlanetaryTourSystem {
      +createQuery(startCoord, endCoord, corridorWidth)
      +collectImages(boundary)
      +normalizeImages(imageSet)
      +orderByTraverse(imageSet)
      +displayTour()
  }
  class ImageSource {
      <<interface>>
      +getImagesByRegion()
  }
  class RoverImageDB {
      -roverName: string
  }
  class OrbiterImageDB {
      -instrument: string
  }
  
  ImageSource <|.. RoverImageDB
  ImageSource <|.. OrbiterImageDB
  PlanetaryTourSystem ..> ImageSource : uses
  

3.2. AgTech: Crop Phenotyping and Growth Monitoring

• Enabling Description: This system creates a time-lapse virtual tour of crop development over a growing season. The 'start point' is "planting date" and the 'end point' is "harvest date." The 'boundary' is a specific farm field defined by GPS coordinates. Images are collected from a heterogeneous set of sources: daily satellite imagery (e.g., from Planet Labs), weekly drone flyovers, and fixed-position IoT cameras within the field. The system orders the images primarily by their timestamp, creating a sequential view of the crop's growth. The user can set the 'image density' to 'one composite image per day' to track key growth stages and identify anomalies like pest infestation or nutrient deficiency.

• Mermaid Diagram:

  gantt
      title Crop Growth Virtual Tour
      dateFormat  YYYY-MM-DD
      axisFormat %m-%d
      section Field A
      Planting         :done, p1, 2026-04-01, 1d
      Germination Phase:     g1, after p1, 14d
      Vegetative Phase :     v1, after g1, 30d
      Flowering Phase  :     f1, after v1, 20d
      Harvest          :     h1, after f1, 1d
  
      %% Data points represent images collected for the tour
      Satellite Image: crit, 2026-04-10, 1d
      Drone Flyover  : crit, 2026-04-25, 1d
      IoT Camera Snap: crit, 2026-05-15, 1d
      Satellite Image: crit, 2026-05-20, 1d
  

---

4. Integration with Emerging Technology

4.1. Generative AI for Tour Completion

• Enabling Description: This variation addresses gaps in a virtual tour where no images are available. After collecting and ordering existing images, the system identifies segments of the path with a density below a user-defined threshold. For each gap, a conditional Generative Adversarial Network (cGAN) is employed. The cGAN is conditioned on the two images chronologically or spatially bracketing the gap, as well as on underlying map data (e.g., satellite or street view imagery) for that location. It then generates a synthetic, photorealistic image that provides a plausible transition between the real images, resulting in a complete and continuous virtual tour.

• Mermaid Diagram:

  sequenceDiagram
      participant User
      participant TourSystem
      participant GAN_Module
      participant MapAPI
  
      User->>TourSystem: createTour(A, Z)
      TourSystem->>TourSystem: Collect & order images [img1, img5, img10]
      TourSystem->>TourSystem: Identify gap between img1 and img5
      TourSystem->>MapAPI: Get map data for gap location
      MapAPI-->>TourSystem: Satellite/Street View data
      TourSystem->>GAN_Module: GenerateImage(context=img1, context2=img5, mapData)
      GAN_Module-->>TourSystem: Synthetic image [img_synth_3]
      TourSystem->>TourSystem: Insert synthetic image into sequence
      TourSystem->>User: Display completed tour [img1, img_synth_3, img5, ...]
  

4.2. Blockchain for Provenance and Royalties

• Enabling Description: To ensure image authenticity and manage creator rights, this system integrates a blockchain ledger. When an image is submitted for inclusion in a tour, a perceptual hash (e.g., aHash or dHash) is calculated and registered on a smart contract, creating an immutable record of the image content and its creator's wallet address. When a user's query results in a tour that includes the image, the smart contract automatically logs the usage. This framework can be extended to handle micropayments, where viewing a tour triggers a transaction that distributes fractional royalties to the original photographers whose work was included. This establishes a transparent and verifiable marketplace for tour content.

• Mermaid Diagram:

  erDiagram
      USER ||--o{ VIRTUAL_TOUR : creates
      VIRTUAL_TOUR ||--|{ TOUR_IMAGE : contains
      TOUR_IMAGE }o--|| IMAGE_LEDGER : references
      IMAGE_LEDGER {
          string imageHash PK
          string creatorWalletAddress
          datetime timestamp
          string metadataURI
      }
      USER {
          string userID PK
          string walletAddress
      }
  

---

5. Inverse and Failure Mode Operation

5.1. Bandwidth-Optimized "Minimalist Tour"

• Enabling Description: This derivative is designed for low-power or low-bandwidth environments. When the system detects constrained network conditions, it enters a "minimalist" mode. It first selects a drastically reduced subset of images. The selection algorithm prioritizes "keyframe" images that represent significant changes in scenery or direction, discarding visually redundant images. Redundancy is calculated by comparing the perceptual hashes of spatially adjacent images; if the Hamming distance between two hashes is below a threshold, one image is discarded. The remaining images are then heavily compressed before being sent to the client, ensuring a functional, albeit sparse, tour with minimal data consumption.

• Mermaid Diagram:

  flowchart TD
      A[Create Tour Request] --> B{Network Condition Check};
      B -- High Bandwidth --> C[Standard Tour Generation];
      B -- Low Bandwidth --> D[Minimalist Mode];
      D --> E{Select Keyframe Images};
      E --> F{Calculate Perceptual Hashes};
      F --> G{Discard Redundant Images (Low Hamming Distance)};
      G --> H{Aggressive Image Compression};
      H --> I[Display Minimalist Tour];
      C --> J[Display Standard Tour];
  

---

Combination Prior Art Scenarios

1. Combination with OpenStreetMap (OSM) and Overpass API: The user defines the start and end points on an OSM map interface. The system queries the Overpass API to retrieve the specific nodes and ways (roads, paths) that constitute a viable route between the points. The "boundary" for image collection is not a simple corridor but is defined precisely by the geometry of the retrieved OSM route. The final ordering of images is constrained by the sequence of nodes in the OSM data, ensuring the tour perfectly follows a real-world path.

2. Combination with EXIF and IPTC Open Standards: The entire filtering and ordering mechanism is built on open metadata standards, without proprietary data structures. The system exclusively uses embedded EXIF data for GPSLatitude, GPSLongitude, and DateTimeOriginal for spatiotemporal ordering. User-defined filters for content (e.g., "show only sunsets") are implemented as string searches against the ImageDescription and Keywords fields within the standardized IPTC metadata block of each image file.

3. Combination with ActivityPub (Fediverse) Protocol: The system operates as a federated service. A user on one ActivityPub instance (e.g., a "Travel-Tour" server) initiates a query. This query is broadcast as an ActivityPub Question object to other federated instances. Each instance locally searches its public, geotagged images that match the query's boundary and responds. The originating server collects these responses, compiles the images from across the Fediverse, orders them, and presents the final tour. The tour itself can be published as an OrderedCollection object, making it natively shareable across the decentralized network.