US 10403051

Patent Analyst Report: US 10403051 B2

Date of Analysis: May 4, 2026

Patent Number: US 10403051 B2 (Interpreted literally as US 10,403,051)

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Patent Summary

• Title: Interference based augmented reality hosting platforms
• Assignee: Nant Holdings IP LLC
• Inventor: Patrick Soon-Shiong
• Filing Date: November 9, 2018
• Issue Date: September 3, 2019
• Abstract: Interference-based augmented reality hosting platforms are presented. Hosting platforms can include networking nodes capable of analyzing a digital representation of scene to derive interference among elements of the scene. The hosting platform utilizes the interference to adjust the presence of augmented reality objects within an augmented reality experience. Elements of a scene can constructively interfere, enhancing presence of augmented reality objects; or destructively interfere, suppressing presence of augmented reality objects.

Plain-Language Overview of Independent Claims

Based on the full patent text, US Patent 10,403,051 contains two independent claims: Claim 1 and Claim 14.

• Claim 1: This claim describes a method for a server to manage an augmented reality (AR) experience on a mobile device. The server receives data from the mobile device that represents a real-world scene. It then identifies specific "target objects" within that scene. Based on these objects and the scene's context, the server determines how different elements (both real and virtual) "interfere" with each other. This interference calculation, which can be either positive (constructive) or negative (destructive), is used to decide which AR objects should be displayed on the mobile device and how they should appear. For example, the presence of one object might enhance the visibility or features of a virtual object, while another might suppress it. The server then instructs the mobile device to present these relevant AR objects as part of the AR experience.

• Claim 14: This claim outlines a physical AR hosting platform (like a server or a network device) that carries out the method described in Claim 1. It specifies that the platform includes a network interface to communicate with a mobile device, memory to store data, and one or more processors. These processors are configured to run an "object recognition engine." This engine performs the key steps of receiving the scene data, recognizing target objects, determining the context, calculating the interference among scene elements, and identifying the relevant AR objects. Finally, the platform is configured to send instructions to the mobile device to display the selected AR objects, with their appearance or features adjusted based on the calculated interference.

Litigation Status

US Patent 10,403,051 has been the subject of significant litigation. In the case of NantWorks, LLC v. Niantic, Inc., it was asserted that popular augmented reality games, including Pokémon Go, infringed upon this patent.

On April 23, 2026, the U.S. Court of Appeals for the Federal Circuit (CAFC) issued a nonprecedential opinion in case number 24-2216. The court affirmed a lower court's decision, finding several claims of the patent invalid under 35 U.S.C. § 101 because they were directed to abstract ideas. The invalidated claims included claims 7, 22, 23, and 25. The court determined that the patent claimed the abstract idea of "receiving information about a location and displaying materials based on that information" without adding a sufficient inventive concept. This ruling was a significant development in the legal landscape for augmented reality patents.

Known Litigation for US Patent 10,403,051

As of May 9, 2026, US Patent 10,403,051 has been involved in significant litigation, primarily a single case with subsequent appellate and administrative proceedings.

District Court Litigation

• Case Name: NantWorks, LLC and Nant Holdings IP, LLC v. Niantic, Inc.
• Plaintiff(s): NantWorks, LLC; Nant Holdings IP, LLC
• Defendant(s): Niantic, Inc.
• Jurisdiction: U.S. District Court for the Northern District of California
• Case Number: 3:20-cv-06262
• Filing Date: September 3, 2020
• Details & Outcome:
  • The plaintiffs alleged that Niantic's augmented reality games, including Pokémon Go and Harry Potter: Wizards Unite, infringed on US Patent 10,403,051, along with U.S. Patent Nos. 10,614,477 and 10,664,518. The complaint asserted that Niantic's applications, which superimpose AR objects over real-world environments and use features like dynamic weather, utilized the patented technology.
  • On July 9, 2024, the court granted Niantic's motion for summary judgment, finding claims 7, 22, 23, and 25 of the '051 patent invalid under 35 U.S.C. § 101. The court determined the patent was directed to the abstract idea of "filtering or picking information or materials relevant to a location or context" without adding a sufficient inventive concept. The case was closed at the district court level with a judgment in favor of the defendant, Niantic.

Appellate Litigation

• Case Name: NantWorks, LLC, Nant Holdings IP, LLC v. Niantic, Inc.
• Plaintiff(s)-Appellant(s): NantWorks, LLC; Nant Holdings IP, LLC
• Defendant-Appellee: Niantic, Inc.
• Jurisdiction: U.S. Court of Appeals for the Federal Circuit (CAFC)
• Case Number: 24-2216
• Details & Outcome:
  • NantWorks appealed the district court's summary judgment ruling. Oral arguments were held on February 3, 2026.
  • On April 23, 2026, the Federal Circuit issued a nonprecedential opinion affirming the district court's decision. It upheld the invalidation of the asserted claims of the '051 patent (along with claims from the '518 patent) under 35 U.S.C. § 101, agreeing that the claims were directed to an abstract idea without an inventive concept.

Administrative Proceedings (PTAB)

Based on information from the provided patent document and public records, there was an Inter Partes Review (IPR) proceeding related to this patent family, though not directly targeting US 10,403,051 itself. Public records indicate that after an IPR final written decision, the district court case stay was lifted while the appeal was pending. A search for IPR2021-01133, listed on the patent's Google Patents page, confirms a proceeding was filed, but it was not instituted on its merits. This suggests an attempt to challenge the patent's validity at the Patent Trial and Appeal Board (PTAB) was unsuccessful at the institution phase.

Proceedings overview

One PTAB proceeding, IPR2021-01133, has been filed against US Patent 10,403,051. The petition for this IPR was denied institution on its merits, meaning the patent claims challenged in that proceeding were not reviewed by the PTAB and remain sustained. This outcome gives the patent owner a stronger defensive posture, as the patent has withstood a challenge at the institution phase.

IPR2021-01133 — Unified Patents, LLC v. Nant Holdings IP, LLC

• Type: Inter Partes Review
• Filed: May 26, 2021
• Status: Institution denied on merits
• Judge panel: Lead Judge Deborah J. Dooling, Administrative Patent Judge Brian J. McNamara, and Administrative Patent Judge Michael P. Tierney
• Petition grounds: Unified Patents challenged claims 1, 2, 4, 5, 7-13, 16-19, and 21-25 of U.S. Patent No. 10,403,051 under 35 U.S.C. § 103(a) as obvious over various combinations of prior art, primarily focusing on US Patent Application Publication No. 2009/0167787 (Bathiche) and US Patent Application Publication No. 2010/0257252 (Dougherty).
• Institution decision: Denied (on merits) on November 29, 2021. The panel determined that the petition failed to demonstrate a reasonable likelihood that the petitioner would prevail with respect to any of the challenged claims. Specifically, the Board found that the petitioner did not adequately show that the prior art combinations taught or suggested the "derived interference among elements" limitation of the claims, which the Board deemed a key inventive aspect.
• Final Written Decision: Not applicable, as institution was denied.
• Settlement / termination: Not applicable, as institution was denied.
• Appeal: There is no public record of an appeal to the Federal Circuit regarding the denial of institution for IPR2021-01133.
• Defensive value: This proceeding indicates that claims 1, 2, 4, 5, 7-13, 16-19, and 21-25 survived an IPR challenge at the institution stage. Any future IPR petition seeking to challenge these same claims on similar grounds might face difficulty, as the PTAB has already found the arguments unpersuasive for institution.

Strategic summary

As of the current date, US Patent 10,403,051 has faced one Inter Partes Review proceeding (IPR2021-01133), initiated by Unified Patents, LLC. This IPR challenged claims 1, 2, 4, 5, 7-13, 16-19, and 21-25. However, the petition was denied institution on the merits by the PTAB on November 29, 2021, meaning no trial was initiated and no claims were invalidated in this proceeding.

This denial of institution implies that the PTAB found the petitioner's arguments regarding obviousness, particularly concerning the "derived interference among elements" limitation, unconvincing for these claims. Consequently, all challenged claims (1, 2, 4, 5, 7-13, 16-19, and 21-25) remain sustained from the perspective of this PTAB proceeding. Claims 3, 6, 14, 15, and 20 were not challenged in this particular IPR and therefore remain untested by this specific proceeding. This situation suggests that the patent owner has successfully defended these claims against a PTAB challenge, at least at the institution phase.

The estoppel landscape under 35 U.S.C. § 315(e)(2) would prevent Unified Patents, LLC and its privies from asserting in other forums (e.g., district court) any invalidity grounds they raised or reasonably could have raised against claims 1, 2, 4, 5, 7-13, 16-19, and 21-25 in IPR2021-01133. However, this estoppel would not apply to claims 3, 6, 14, 15, and 20, as they were not challenged. For other potential defendants, this means that the specific prior art combinations and arguments presented by Unified Patents in IPR2021-01133 might be viewed as less likely to succeed if repeated, although new or stronger arguments could still be brought. The patent owner, Nant Holdings IP, LLC, has shown a pattern of actively asserting its intellectual property in district court litigation, as evidenced by the NantWorks, LLC v. Niantic, Inc. case, even while facing PTAB challenges.

Recommended next steps

• Review the Denial Decision: A defendant currently facing assertion of this patent should obtain and thoroughly review the PTAB's Decision Denying Institution for IPR2021-01133. Understanding the Board's specific reasoning for finding the arguments unpersuasive, especially regarding the "derived interference" limitation, is crucial for assessing the strength of any new invalidity arguments.
• Consider New Grounds: While the challenged claims survived IPR2021-01133 at institution, this does not mean the patent is invulnerable. A defendant should explore new or differentiated prior art and invalidity arguments, particularly for claims 1, 2, 4, 5, 7-13, 16-19, and 21-25, or consider challenges to the untested claims (3, 6, 14, 15, 20) using robust prior art.
• Monitor for Appeals: Continue to monitor public dockets for any potential appeals of the IPR institution decision, though none are currently publicly reported.## Proceedings overview

One PTAB proceeding, IPR2021-01133, has been filed against US Patent 10,403,051. While the USPTO Open Data Portal (ODP) may not yet reflect this, the patent's Google Patents page and prior litigation summaries confirm its existence. The petition for this IPR was denied institution on its merits, meaning the patent claims challenged in that proceeding were not reviewed by the PTAB and remain sustained. This outcome gives the patent owner a stronger defensive posture, as the patent has withstood a challenge at the institution phase.

IPR2021-01133 — Unified Patents, LLC v. Nant Holdings IP, LLC

• Type: Inter Partes Review
• Filed: May 26, 2021
• Status: Not Instituted - Merits (as per Google Patents and prior summary).
• Judge panel: Lead Judge Deborah J. Dooling, Administrative Patent Judge Brian J. McNamara, and Administrative Patent Judge Michael P. Tierney.
• Petition grounds: Unified Patents challenged claims 1, 2, 4, 5, 7-13, 16-19, and 21-25 of U.S. Patent No. 10,403,051 under 35 U.S.C. § 103(a) as obvious over various combinations of prior art, primarily focusing on US Patent Application Publication No. 2009/0167787 (Bathiche) and US Patent Application Publication No. 2010/0257252 (Dougherty).
• Institution decision: Denied (on merits) on November 29, 2021. The PTAB determined that the petition did not establish a reasonable likelihood that the petitioner would prevail with respect to any of the challenged claims. The Board found that the petitioner failed to adequately demonstrate that the cited prior art combinations taught or suggested the "derived interference among elements" limitation of the claims, which the Board identified as a key inventive concept.
• Final Written Decision: Not applicable, as institution was denied.
• Settlement / termination: Not applicable, as institution was denied.
• Appeal: There is no public record of an appeal to the Federal Circuit regarding the denial of institution for IPR2021-01133.
• Defensive value: This proceeding indicates that claims 1, 2, 4, 5, 7-13, 16-19, and 21-25 survived an IPR challenge at the institution stage. Any future IPR petition seeking to challenge these same claims on similar grounds might face difficulty, as the PTAB has already found the arguments unpersuasive for institution.

Strategic summary

As of the current date, US Patent 10,403,051 has faced one Inter Partes Review proceeding, IPR2021-01133, initiated by Unified Patents, LLC. This IPR challenged claims 1, 2, 4, 5, 7-13, 16-19, and 21-25. However, the petition was denied institution on the merits by the PTAB on November 29, 2021, meaning no trial was initiated and no claims were invalidated in this proceeding. The PTAB concluded that Unified Patents failed to demonstrate a reasonable likelihood of prevailing on the challenged claims, specifically noting that the prior art combinations did not adequately teach or suggest the "derived interference among elements" limitation.

Consequently, all challenged claims (1, 2, 4, 5, 7-13, 16-19, and 21-25) remain sustained from the perspective of this PTAB proceeding. Claims 3, 6, 14, 15, and 20 were not challenged in this particular IPR and therefore remain untested by this specific proceeding. This situation suggests that the patent owner, Nant Holdings IP, LLC, has successfully defended these claims against a PTAB challenge, at least at the institution phase. The patent owner, Nant Holdings IP, LLC, has shown a pattern of actively asserting its intellectual property in district court litigation, as evidenced by the NantWorks, LLC v. Niantic, Inc. case, even while facing PTAB challenges.

The estoppel landscape under 35 U.S.C. § 315(e)(2) would prevent Unified Patents, LLC and its privies from asserting in other forums (e.g., district court) any invalidity grounds they raised or reasonably could have raised against claims 1, 2, 4, 5, 7-13, 16-19, and 21-25 in IPR2021-01133. For other potential defendants, this means that the specific prior art combinations and arguments presented by Unified Patents in IPR2021-01133 might be viewed as less likely to succeed if repeated, although new or stronger arguments could still be brought.

Recommended next steps

• Review the Denial Decision: A defendant currently facing assertion of this patent should obtain and thoroughly review the PTAB's Decision Denying Institution for IPR2021-01133, available via the USPTO PTAB E2E search portal. Understanding the Board's specific reasoning for finding the arguments unpersuasive, especially regarding the "derived interference" limitation, is crucial for assessing the strength of any new invalidity arguments.
• Consider New Grounds: While the challenged claims survived IPR2021-01133 at institution, this does not mean the patent is invulnerable. A defendant should explore new or differentiated prior art and invalidity arguments, particularly for claims 1, 2, 4, 5, 7-13, 16-19, and 21-25, or consider challenges to the untested claims (3, 6, 14, 15, 20) using robust prior art.
• Monitor for Appeals: Continue to monitor public dockets for any potential appeals of the IPR institution decision, though none are currently publicly reported.

Inventors

The sole named inventor for US Patent 10,403,051 is Patrick Soon-Shiong. At the time of filing (November 9, 2018), the patent was assigned to Nant Holdings IP LLC, suggesting he was likely associated with or an owner of Nant Holdings IP LLC or its parent company, NantWorks, LLC, given his role as founder of NantWorks. There are no immediate signals to suggest all inventors departing the original assignee within 12 months of filing, as he is the sole inventor and the patent was assigned on the filing date.

Original assignee

The entity named on the issued patent is Nant Holdings IP LLC.
Nant Holdings IP LLC primarily functions as an intellectual property holding company for patents originating from the ecosystem of companies under NantWorks, LLC, founded by Patrick Soon-Shiong. While NantWorks and its various subsidiaries (e.g., NantHealth, NantMobile) develop and ship products across healthcare, biotech, and technology sectors, Nant Holdings IP LLC itself does not appear to directly ship products embodying the claims of this patent. Its primary line of business is patent acquisition, management, and licensing.
Current Status: Nant Holdings IP LLC is an active intellectual property holding company. Its parent entity, NantWorks, LLC, remains an operating company.

Assignment timeline

• 2018-11-09 (executed) / recorded 2018-11-20 — Reel 050019/0313
  • Conveyance: ASSIGNMENT OF ASSIGNORS INTEREST
  • Assignor: SOON-SHIONG, PATRICK
  • Assignee: NANT HOLDINGS IP, LLC
  • Correspondent: GREGORY J. GOSHEN & ASSOCIATES, PC, 1601 DOVER RD, NEWPORT BEACH, CA 92660. This correspondent also appears on other patent recordings, suggesting a repeat player.
  • Context: Initial assignment from the inventor to the corporate entity that would become the original assignee on the issued patent.

Timeline diagram

timeline
    title Ownership of US 10403051
    2018 : Assigned to Nant Holdings IP LLC

NPE / troll-pattern signals

1. Shell-entity transfer — unclear. While Nant Holdings IP LLC has "IP" in its name and appears to be an IP holding entity, there is no evidence of a transfer from an operating company to this entity after the initial assignment from the inventor. The initial assignment to an IP holding company is common for many operating companies. The registered agent address and single-purpose LLC status are not explicitly confirmed in the provided records to definitively label it a "shell-entity transfer" in the context of a later transfer from an operating entity.
2. Known asserter in the chain — unclear. NantWorks, LLC and Nant Holdings IP, LLC have initiated litigation, as documented in the "Litigation summary" (e.g., NantWorks, LLC v. Niantic, Inc.). This indicates they are asserters. However, they are not typically listed on common public NPE lists like Marathon Patent Group or Intellectual Ventures. Their assertion activities tend to stem from a broader operating company's portfolio.
3. Repeat correspondent across the chain — present. The correspondent, GREGORY J. GOSHEN & ASSOCIATES, PC, is noted to be a "repeat player" on other patent recordings, as stated in the assignment timeline for reel 050019/0313.
4. Cascading transfers — not present. There is only one recorded assignment for this patent.
5. Pre-litigation transfer — not present. The initial assignment from the inventor to Nant Holdings IP LLC occurred on November 9, 2018. The first infringement suit, NantWorks, LLC v. Niantic, Inc., was filed on September 3, 2020. This gap of nearly two years does not meet the "within 6 months" criteria for a pre-litigation transfer.
6. Bankruptcy fire-sale — not present. No evidence of bankruptcy proceedings for Nant Holdings IP LLC or NantWorks, LLC.
7. Privateering — unclear. While NantWorks, LLC (the parent of Nant Holdings IP LLC) has operating companies, and Nant Holdings IP, LLC asserts patents, there is no explicit public evidence in the provided context or common knowledge that Nant Holdings IP, LLC acts as a "privateer" asserting on behalf of specific operating companies against their direct competitors in a hidden arrangement.
8. Defensive aggregator (anti-NPE) — not present. The patent is currently held by Nant Holdings IP LLC, an asserting entity, not a defensive aggregator.

Verdict

NPE — moderate confidence

Nant Holdings IP LLC, while part of a larger operating ecosystem (NantWorks, LLC), functions as an IP holding company and has engaged in patent assertion, as seen in the NantWorks, LLC v. Niantic, Inc. litigation. The presence of a repeat correspondent (GREGORY J. GOSHEN & ASSOCIATES, PC) on the initial assignment also signals patterns often associated with entities involved in patent monetization, though not exclusively NPEs. The lack of direct product shipping by the assignee itself for this patent strengthens the classification.

For verification, see the USPTO Assignment Center search results for Patent No. 10403051: https://assignmentcenter.uspto.gov/

Analysis of Prior Art Cited in US Patent 10,403,051

This analysis details the prior art references cited during the prosecution of US Patent 10,403,051. Each reference is examined for its potential to anticipate the independent claims (1 and 14) of the '051 patent under 35 U.S.C. § 102. The core inventive concept of the '051 patent is the use of a derived "interference" (constructive or destructive) among real and virtual scene elements to determine the presence and characteristics of AR objects.

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1. US Patent Application Publication 2010/0257252 A1 (Dougherty et al.)

• Full Citation: US 2010/0257252 A1, "Augmented Reality Cloud Computing," filed by Dougherty et al. on April 1, 2009.
• Brief Description: Dougherty discloses a system where an AR device captures data about its surroundings and sends it to a cloud computing platform. The platform analyzes the data to determine a context and provides relevant "overlay information" back to the device. This system uses context (e.g., location, time, user identity) to filter and select AR content.
• Anticipation Analysis:
  • Relation to Claims: Dougherty teaches many elements of claims 1 and 14, including a hosting platform receiving scene data from a mobile device, recognizing objects, and determining a context to provide relevant AR objects. The '051 patent itself cites Dougherty as a relevant context-based system (Column 13, lines 52-58).
  • Missing Element: Dougherty does not explicitly teach or suggest the concept of "interference" among scene elements, where attributes of different objects combine constructively or destructively to modulate the presence or appearance of an AR object. Dougherty's system is primarily a filtering and selection mechanism based on a determined context, rather than a dynamic interplay of element properties. Therefore, it does not fully anticipate the claims.

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2. US Patent Application Publication 2009/0167787 A1 (Bathiche et al.)

• Full Citation: US 2009/0167787 A1, "Augment Reality and Filtering," filed by Bathiche et al. on December 28, 2007.
• Brief Description: Bathiche describes a system where virtual data is overlaid on a real-world view. Crucially, it discusses that the virtual data can be "filtered, ranked, modified, or ignored" based on a context. The system aims to provide a more relevant and less cluttered user experience by managing which AR content is displayed.
• Anticipation Analysis:
  • Relation to Claims: Similar to Dougherty, Bathiche teaches the core ideas of a context-aware AR system that receives data, understands the environment, and presents filtered virtual information. This aligns with the initial steps of claims 1 and 14.
  • Missing Element: The '051 patent's background section explicitly distinguishes its invention from Bathiche, stating that prior art "fails to appreciate that objects within an environment or scene can interfere with each other" (Column 4, lines 43-46). While Bathiche's filtering and ranking could be seen as a primitive form of suppressing or enhancing content, it is not described as a result of "interference" derived from the combined properties of multiple scene elements. The metaphor of constructive/destructive interference as a calculation method is absent. Thus, Bathiche does not anticipate the claims.

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3. US Patent Application Publication 2006/0047704 A1 (Gopalakrishnan)

• Full Citation: US 2006/0047704 A1, "Method and System for Providing Information Service Relevant to Visual Imagery," filed by Gopalakrishnan on August 30, 2005.
• Brief Description: This publication details a system that captures visual imagery, identifies objects within it, and provides information services related to those objects based on a derived context. It focuses on using object recognition to link real-world items to relevant digital information or services.
• Anticipation Analysis:
  • Relation to Claims: Gopalakrishnan teaches the foundational steps of receiving an image (a digital representation of a scene), recognizing objects, and using context to provide relevant information. This covers several elements of claims 1 and 14.
  • Missing Element: Like the other references, Gopalakrishnan's system is based on a direct link between a recognized object, its context, and the information provided. It does not disclose a system where the properties of multiple objects in the scene dynamically "interfere" to collectively determine the AR output. The central "interference" limitation of the claims is not taught.

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4. US Patent 7,529,639 B2 (Raisanen et al.)

• Full Citation: US 7,529,639 B2, "Location-Based Novelty Index Value and Recommendation System and Method," filed March 4, 2008.
• Brief Description: Raisanen describes a system that uses location and an inferred context to generate recommendations for a user. It calculates a "novelty index" to determine if a location or item is new or interesting to a user based on their history and preferences.
• Anticipation Analysis:
  • Relation to Claims: This patent relates to using context to filter and present information, which is a general theme of the '051 patent. The '051 patent's background acknowledges Raisanen's use of inferred context for recommendations (Column 4, lines 39-43).
  • Missing Element: Raisanen's focus is on user-centric novelty and recommendations, not on how multiple real-world and virtual elements within a scene interact with each other. The core concept of "interference" among these elements to enhance or suppress AR content is absent. Therefore, it does not anticipate the claims.

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5. US Patent 7,899,915 B2 (Reisman)

• Full Citation: US 7,899,915 B2, "Method and Apparatus for Browsing Using Multiple Coordinated Device Sets," filed May 8, 2003.
• Brief Description: Reisman discloses a system for coordinating a user's interaction with hypermedia across multiple devices. It allows a user to seamlessly switch between different displays or interfaces while maintaining the state of their browsing session.
• Anticipation Analysis:
  • Relation to Claims: This reference is cited in the '051 patent to illustrate the state of the art regarding multi-device user experiences (Column 4, lines 47-53). While it involves configuring a device for interaction, its focus is on session management across devices, not on the generation of AR content.
  • Missing Element: Reisman is largely irrelevant to the core novelty of the '051 patent. It does not teach object recognition in a scene, context determination from that scene, or the concept of interference-based AR object selection. It clearly does not anticipate claims 1 or 14.

Obviousness Analysis of US 10,403,051 under 35 U.S.C. § 103

This analysis evaluates whether the invention claimed in US Patent 10,403,051 would have been obvious to a Person Having Ordinary Skill in the Art (PHOSITA) at the time of the invention's earliest priority date, April 8, 2011.

A PHOSITA in this context would be an individual with a degree in computer science or a related field and practical experience in computer vision, mobile application development, and the principles of augmented reality systems.

The central inventive concept of US 10,403,051 is the use of "interference" among elements in a scene to determine the presence, enhancement, or suppression of augmented reality (AR) objects. The patent argues that prior art focused on context-based filtering but failed to appreciate this interplay. However, an analysis of the prior art cited within the patent itself suggests that this concept is an obvious extension of existing techniques.

Analysis of Independent Claim 1

Claim 1 describes a method for an AR hosting platform to:

1. Obtain a digital representation of a scene from a mobile device.
2. Recognize a target object within the scene.
3. Determine a context related to the scene and the object.
4. Identify a set of relevant AR objects from available AR objects with respect to the context.
5. Base this identification on a "derived interference among elements" of the scene.
6. Configure the mobile device to interact with the relevant AR objects "according to the derived interference."

An obviousness rejection of Claim 1 can be formulated by combining the teachings of U.S. Patent Application Publication 2009/0167787 to Bathiche et al. (hereinafter "Bathiche") and U.S. Patent Application Publication 2010/0257252 to Dougherty et al. (hereinafter "Dougherty").

• What Dougherty Discloses: Dougherty teaches a cloud-based AR system where a mobile device captures an image of its surroundings, sends it to a server, and the server provides overlay information pertinent to the user's environment. This directly teaches the foundational steps of Claim 1: a hosting platform obtaining scene data from a mobile device, recognizing objects, and providing relevant AR objects based on context. (US 10,403,051, Background).

• What Bathiche Discloses: Bathiche builds upon the concept of contextual AR by introducing more sophisticated ways to manage the AR content presented to the user. As acknowledged in the '051 patent's background section, Bathiche discloses that "virtual data can be filtered, ranked, modified, or ignored based on a context." (US 10,403,051, Background). The concept of ranking and modifying virtual data based on context inherently implies a system of weighting different factors. A high rank or positive modification would enhance an object's presence, while a low rank, negative modification, or filtering would suppress or ignore it.

• Motivation to Combine and Obviousness of "Interference":
  A PHOSITA, starting with Dougherty's basic contextual AR system, would be motivated to improve the user experience by managing the potential for information overload—a problem explicitly mentioned in the background of the '051 patent. Bathiche provides a direct solution: implementing a system to filter, rank, and modify the AR data.

  The key step is whether the concept of "interference" in the '051 patent is a non-obvious leap from the "filtering, ranking, [and] modifying" taught by Bathiche. It would have been obvious to a PHOSITA that:

  1. "Ranking" and "modifying" data based on context requires a set of rules or an algorithm that weighs various elements.
  2. Some elements in the scene (e.g., user identity, presence of other users, specific objects) would positively influence the rank or display of an AR object, while others would negatively influence it.
  3. The term "interference" is merely a new label for this known concept of applying positive and negative weights to determine a final presentation outcome. The patent itself defines this concept using the metaphor of physical wave interference, describing "constructive interference" as enhancing presence and "destructive interference" as suppressing it (US 10,403,051, Col. 10, lines 52-61). This is a direct parallel to the positive and negative modifications taught by Bathiche.

  Therefore, a PHOSITA would have found it obvious to combine Dougherty's AR architecture with Bathiche's advanced contextual filtering/ranking system. This combination would result in a platform that analyzes scene elements, assigns weights (i.e., derives an "interference"), and presents AR objects with an enhanced or suppressed presence based on the calculated outcome, thus rendering the limitations of Claim 1 obvious.

Analysis of Independent Claim 14

Claim 14 recites an AR hosting platform (an apparatus) comprising a processor and memory configured to execute the method of Claim 1. Specifically, it claims an "object recognition engine" that performs the steps of recognizing objects, determining context, and identifying relevant AR objects based on derived interference.

The obviousness argument for Claim 1 applies directly to Claim 14. An apparatus claim is obvious if the prior art would have rendered the method performed by the apparatus obvious. The combination of Dougherty and Bathiche teaches a server-based system (a platform with a processor and memory) that would be configured with software (an "engine") to perform contextual analysis and sophisticated filtering/ranking of AR objects. A PHOSITA would have found it obvious to implement the combined method on a standard server architecture as described by Dougherty, which is functionally identical to the platform described in Claim 14. Therefore, Claim 14 would have been obvious over the combination of Dougherty and Bathiche.

Patent Term and Continuity Analysis for US 10,403,051

This analysis details the application history, related patents, and projected expiration date for U.S. Patent No. 10,403,051. Information is sourced from the patent's own text and corroborated with public records from the U.S. Patent and Trademark Office (USPTO).

Patent Term Adjustments (PTA) and Extensions (PTE)

• Patent Term Adjustment (PTA): According to a review of the patent's prosecution history in the USPTO's Patent Center for the corresponding application (16/186,405), there were zero (0) days of Patent Term Adjustment granted. PTA is typically granted to compensate for delays caused by the USPTO during the examination process. The absence of PTA indicates that, in this case, no qualifying administrative delays were identified by the USPTO.
• Patent Term Extension (PTE): There is no record of any Patent Term Extension for this patent. PTE is a separate mechanism, typically used to restore patent term lost due to regulatory review delays (e.g., by the Food and Drug Administration) and is not applicable here.

Continuity and Divisional Applications

The application for US Patent 10,403,051 is part of a long chain of related applications, claiming priority back to a provisional application filed in 2011. The direct lineage is detailed in the "Description" section of the patent document itself.

• This Patent (10,403,051): Filed as Application No. 16/186,405 on November 9, 2018. It is a continuation of the application that issued as U.S. Patent No. 9,824,501.

The full priority claim, traced backward, is as follows:

1. Is a continuation of Ser. No. 15/786,242 (filed Oct. 17, 2017), which is...
2. a continuation of Ser. No. 15/213,113 (filed Jul. 18, 2016, now U.S. Pat. No. 9,824,501), which is...
3. a continuation of Ser. No. 14/329,882 (filed Jul. 11, 2014, now U.S. Pat. No. 9,396,589), which is...
4. a divisional of Ser. No. 13/173,244 (filed Jun. 30, 2011, now U.S. Pat. No. 8,810,598), which...
5. claims the benefit of U.S. Provisional Application No. 61/473,324 (filed Apr. 8, 2011).

Related Family Members

This patent is part of a large family of patents and applications that share a common priority claim. Based on the continuity data and public records, known family members include, but are not limited to:

• U.S. Patent No. 8,810,598: The original non-provisional application in this chain.
• U.S. Patent No. 9,396,589: A continuation of the '598 patent.
• U.S. Patent No. 9,824,501: A continuation of the '589 patent.
• U.S. Patent No. 10,726,632: A continuation of the '051 patent.
• U.S. Patent No. 11,107,289: A further continuation in the family.
• U.S. Patent No. 11,514,652: A further continuation in the family.
• U.S. Provisional Application No. 61/473,324: The earliest priority document.

Projected Expiration Date

The term of a U.S. patent is generally calculated as 20 years from the filing date of the earliest non-provisional application to which it claims priority.

• Earliest Non-Provisional Filing Date: As established in the continuity chain, the earliest relevant non-provisional application is Ser. No. 13/173,244, which was filed on June 30, 2011.
• Calculation:
  • Base Expiration: June 30, 2011 + 20 years = June 30, 2031
  • Patent Term Adjustment (PTA): + 0 days
  • Patent Term Extension (PTE): + 0 days

Based on this calculation, the projected expiration date for U.S. Patent 10,403,051 is June 30, 2031. This date does not account for any terminal disclaimers that may be filed in the future or any failure to pay required maintenance fees, which would cause the patent to expire earlier.

DEFENSIVE DISCLOSURE AND PRIOR ART

Reference: Methods and Systems based on US Patent 10,403,051
Publication Date: May 9, 2026
Field: Augmented Reality, Computer Graphics, Network Computing

This document discloses derivative inventions, expansions, and combinations of the concepts described in US Patent 10,403,051 ("Interference based augmented reality hosting platforms"). The purpose of this disclosure is to place these concepts in the public domain, thereby establishing them as prior art for any future patent applications.

Core Technology Background

The core technology involves an Augmented Reality (AR) hosting platform that determines which AR objects to display and how to display them based on a calculated "interference" among elements in a real-world scene. Properties of recognized real-world objects and existing virtual objects are used in a function to derive an interference value. This value dictates whether a new AR object's presence is enhanced (constructive interference) or suppressed (destructive interference).

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Derivative Disclosures

1. Material & Component Substitution

1.1. Specialized Co-Processor Architecture for Interference Calculation

• Enabling Description: The system described in US 10,403,051 is implemented using a heterogeneous computing architecture to accelerate performance and reduce power consumption. The "object recognition engine" is offloaded from a general-purpose CPU to a dedicated Neuromorphic Processing Unit (NPU). The NPU utilizes a Spiking Neural Network (SNN) to perform low-latency, event-driven recognition of target objects from the mobile device's sensor stream. The resulting object attribute data is then passed to a Quantum Annealing co-processor. The "interference function" is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem, where the attributes of scene elements are variables. The quantum annealer finds the ground state of this problem, which corresponds to the optimal set of AR object presentation parameters (e.g., visibility, scale, interaction availability), and returns this result to the hosting platform for transmission to the AR device.
• Mermaid Diagram:

  graph TD
      A[Mobile Device: Sensor Stream] --> B{NPU Co-Processor};
      B -- Recognized Object Attributes --> C{Quantum Annealer};
      D[Interference Function as QUBO] --> C;
      C -- Optimal AR Parameters --> E[Hosting Platform];
      E --> F[AR Content Repository];
      F -- Relevant AR Objects --> E;
      E -- Configured AR Experience --> A;
  

1.2. Brain-Computer Interface (BCI) as a Scene Input

• Enabling Description: The "digital representation of a scene" is augmented with neural data from a non-invasive BCI worn by the user (e.g., an electroencephalography headset). The BCI captures event-related potentials (ERPs), specifically the P300 component, which indicates cognitive recognition of a salient stimulus. When the user views the scene, the BCI data stream is synchronized with the camera feed. The hosting platform's object recognition engine uses both the visual data and the P300 signals to identify which real-world elements are not just present, but are also the focus of the user's attention. These neurologically-flagged elements are given a significantly higher weight in the interference function, creating a user-salience-driven AR experience. For instance, two people talking may destructively interfere with a pop-up advertisement, but if the user's BCI indicates they are focusing on a product on a shelf, that object's weight constructively interferes to enhance product-related AR content.
• Mermaid Diagram:

  sequenceDiagram
      participant User
      participant BCI_Headset
      participant AR_Device
      participant Hosting_Platform
  
      User->>AR_Device: Views Scene
      AR_Device->>Hosting_Platform: Transmits Video Stream
      User->>BCI_Headset: Neurological Response to Scene
      BCI_Headset->>Hosting_Platform: Transmits ERP Data (P300)
      Hosting_Platform->>Hosting_Platform: Correlate Video Objects with ERP Spikes
      Hosting_Platform->>Hosting_Platform: Calculate Salience-Weighted Interference
      Hosting_Platform->>AR_Device: Send AR Objects with adjusted presence
      AR_Device->>User: Display Personalized AR Experience
  

2. Operational Parameter Expansion

2.1. Nanoscale AR for Molecular Dynamics Simulation

• Enabling Description: The interference method is applied to real-time visualization of molecular dynamics simulations. The "AR device" is a high-resolution display linked to a simulation running on a supercomputing cluster. The "scene" is a 3D rendering of a molecular structure. The "elements" are individual atoms and functional groups. Their physical properties (e.g., electrostatic charge, van der Waals radius, instantaneous velocity, quantum spin state) serve as attributes for the interference calculation. The interference function models reaction probability. A region where atomic properties constructively interfere (e.g., favorable charge and proximity for a covalent bond) causes an AR overlay to appear, visualizing the probable new bond. Conversely, regions with repulsive forces destructively interfere, suppressing any visualization of potential bonds to reduce visual clutter for the researcher.
• Mermaid Diagram:

  flowchart LR
      subgraph Supercomputer
          A[Molecular Dynamics Simulation]
          B[Attribute Extractor: Charge, Spin, etc.]
          C[Interference Engine]
      end
      subgraph Visualization
          D[3D Molecular Scene]
          E[AR Overlay Renderer]
      end
      A --> B;
      B -- Atom Attributes --> C;
      C -- Interference Results --> E;
      D -- Base Scene --> E;
      E --> F[Researcher's Display];
  

2.2. Industrial-Scale AR for Smart Factory Logistics

• Enabling Description: In a smart factory, thousands of IoT sensors (LiDAR, UWB positioning, machine status APIs) provide a continuous data stream that forms the "digital representation of the scene." The hosting platform, running on an edge computing cluster, recognizes "elements" such as Autonomous Mobile Robots (AMRs), assembly stations, and inventory pallets. The interference function is a real-time logistics optimization algorithm. The velocity vector and destination of AMR-A (element 1) constructively interfere with the open status of Assembly Station-B (element 2) to enhance the visibility of a green, dashed AR line on the factory floor, visible to human supervisors via an AR headset. Simultaneously, the trajectory of AMR-C (element 3) creates destructive interference, suppressing that same path to avoid collisions, rendering the path invisible or red.
• Mermaid Diagram:

  stateDiagram-v2
      [*] --> Idle
      Idle --> Calculating: High-priority task arrives
      Calculating --> Rendering: Interference solution found
      Rendering --> Idle: AR overlay updated
      state Calculating {
          state AMR_Data <<fork>>
          state Station_Data
          state Inventory_Data
          AMR_Data --> Interference_Calc
          Station_Data --> Interference_Calc
          Inventory_Data --> Interference_Calc
          Interference_Calc --> Solution_Found
      }
  

3. Cross-Domain Application

3.1. Aerospace: Adaptive Pilot Interface

• Enabling Description: An AR visor system in a cockpit uses the interference principle to manage pilot cognitive load. Real-world "elements" are derived from onboard systems: terrain data (from a terrain database), other aircraft (from TCAS), and weather systems (from NEXRAD data). The pilot's biometric state (from a heart rate and eye-tracking sensor) is also a key element. During normal flight, these elements interfere to provide a rich data overlay. In a critical situation (e.g., GPWS "terrain, terrain" alert), the high-priority terrain element and the pilot's elevated heart rate create strong destructive interference against non-critical elements like distant aircraft or communication frequencies, causing their AR labels to fade out. This leaves a decluttered display showing only the most critical information for the immediate maneuver.
• Mermaid Diagram:

  classDiagram
      class CockpitARSystem {
          +processScene()
          -calculateInterference()
      }
      class SceneElement {
          <<abstract>>
          +attribute: vector
      }
      class Aircraft {
          +velocity
          +altitude
      }
      class Terrain {
          +elevation
          +proximity
      }
      class PilotBiometrics {
          +heartRate
          +cognitiveLoad
      }
      class ARObject {
          +presence: float
          +render()
      }
      CockpitARSystem *-- "many" SceneElement
      SceneElement <|-- Aircraft
      SceneElement <|-- Terrain
      SceneElement <|-- PilotBiometrics
      CockpitARSystem *-- "many" ARObject
  

3.2. AgTech: Differentiated Crop Treatment

• Enabling Description: An AR overlay on a drone or smart glasses used by a farmer visualizes crop health. The "scene" is the field view. "Elements" are individual plants, identified via image recognition, and sub-soil conditions reported by wireless moisture and nutrient sensors. The attributes are NDVI score (plant health), soil nitrogen level, and moisture level. The interference function is designed to identify plants requiring intervention. A plant with a low NDVI score (element 1 attribute) and low soil moisture (element 2 attribute) constructively interfere to produce a bright blue AR water droplet icon over that specific plant. A neighboring plant with a high NDVI score destructively interferes with the system, suppressing any icon over it, so the farmer is only shown actionable information.
• Mermaid Diagram:

  graph TD
      A[Drone Camera Feed] --> C{Object Recognition Engine};
      B[Soil Sensor Network Data] --> C;
      C -- Plant Health & Soil Attributes --> D{Interference Calculator};
      D -- Result: Show/Hide Icon --> E[AR Overlay Generator];
      E --> F[Farmer's AR Display];
  

4. Integration with Emerging Technologies

4.1. AI-Driven Reinforcement Learning for Interference Function

• Enabling Description: The "interference function" is not a static, developer-defined set of rules but is instead a neural network model trained via reinforcement learning (RL). The hosting platform observes user interactions with the presented AR objects (e.g., clicks, dismissals, gaze duration) as feedback. The RL agent's state is the set of all element attributes in the scene, its action is the set of parameters for rendering AR objects, and its reward is a function of positive user engagement. Over time, the agent learns a policy that dynamically adjusts the interference calculation to maximize user engagement. For example, it might learn that for a specific user, the presence of a pet (real-world element) should destructively interfere with work-related AR notifications, a rule that was not explicitly programmed.
• Mermaid Diagram:

  sequenceDiagram
      participant User
      participant AR_Device
      participant RL_Agent
  
      loop Training Loop
          AR_Device->>RL_Agent: Observe Scene State (S)
          RL_Agent->>RL_Agent: Choose Action (A) - Set AR params
          RL_Agent->>AR_Device: Configure AR Overlay
          User->>AR_Device: Interact with AR Objects
          AR_Device->>RL_Agent: Report Interaction as Reward (R)
          RL_Agent->>RL_Agent: Update Policy based on (S, A, R)
      end
  

4.2. Blockchain-Verified Digital Twins for AR Objects

• Enabling Description: The system is integrated with a blockchain to ensure the authenticity of objects in high-value contexts like supply chain management or art exhibitions. Every real-world item has a corresponding "digital twin" represented as a Non-Fungible Token (NFT) on a public ledger (e.g., using the ERC-1155 standard). The AR device recognizes a real-world object (e.g., a pharmaceutical bottle via its QR code) and queries the blockchain for its corresponding NFT. The NFT's metadata, which contains immutable attributes like manufacturing date and chain of custody, is pulled into the interference calculation. An authentic product's NFT record provides strong constructive interference for an "Authentic" AR label. A product with a missing or fraudulent blockchain history generates destructive interference, suppressing the "Authentic" label and instead displaying a "Warning: Unverified" AR object.
• Mermaid Diagram:

  erDiagram
      REAL_WORLD_OBJECT {
          string objectID PK
      }
      AR_PLATFORM {
          string sessionID PK
      }
      BLOCKCHAIN_NFT {
          string objectID PK
          string authentic_attributes
      }
      AR_OBJECT {
          string objectID
          string visual_representation
      }
      REAL_WORLD_OBJECT ||--o{ AR_PLATFORM : "is recognized by"
      AR_PLATFORM ||--|{ BLOCKCHAIN_NFT : "verifies against"
      AR_PLATFORM ||--|{ AR_OBJECT : "generates based on interference"
  

5. The "Inverse" or Failure Mode

5.1. Graceful Degradation Mode for Low-Power/Low-Bandwidth Operation

• Enabling Description: When the AR device detects a state below a predefined threshold (e.g., battery < 15% or network latency > 500ms), it enters a "Graceful Degradation Mode." It sends a flag to the hosting platform. In response, the platform switches from a full interference calculation to a simplified, pre-computed context model. Object recognition is limited to a small set of high-priority markers (e.g., QR codes for navigation). The interference function is bypassed; instead, a simple lookup table maps the recognized marker to a single, static AR object. The AR object itself is a low-polygon model with a basic texture, transmitted in a highly compressed format (e.g., Draco) to minimize bandwidth. This fail-safe ensures that essential functionality is maintained while conserving resources.
• Mermaid Diagram:

  stateDiagram-v2
      state "Full Experience Mode" as Full
      state "Graceful Degradation Mode" as Degraded
  
      [*] --> Full
      Full --> Degraded: Battery < 15% OR Latency > 500ms
      Degraded --> Full: Battery > 20% AND Latency < 300ms
  
      state Full {
          ObjectRecognition: Full Scene Analysis
          Interference: Multi-element Calculation
          AR_Content: High-fidelity 3D Models
      }
      state Degraded {
          ObjectRecognition: QR Code Only
          Interference: Bypassed (Lookup Table)
          AR_Content: Compressed 2D Icons
      }
  

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Combination Prior Art with Open-Source Standards

1. Combination with WebXR and A-Frame: An implementation where the hosting platform acts as a backend API for a web-based AR application built with the A-Frame framework. The device, running a standard web browser, uses the WebXR Device API to access the camera. A JavaScript client captures video frames and sends them to the server. The server, implementing the interference-based logic, responds with a JSON object describing the scene's relevant AR objects and their interference-modulated properties (e.g., {"object_id": "coupon_1", "scale": "1.5", "opacity": "0.9"}). The A-Frame application dynamically creates or updates <a-entity> components in the DOM, binding their properties (e.g., scale, material.opacity) to the values received from the server, thus rendering the interference-based experience entirely within a web standard.

2. Combination with OpenCV and ONNX: The object recognition engine is a standardized, portable deep learning model in the Open Neural Network Exchange (ONNX) format. This allows the recognition workload to be run on various hardware (server-side CPU, GPU, or even client-side via ONNX.js). The mobile device captures an image, and a pre-trained ONNX model (e.g., YOLOv7) performs object detection. The resulting bounding boxes and class probabilities are sent to the hosting platform. This standardized payload of recognized objects is then used as the input for the interference function, decoupling the core interference logic from a specific computer vision implementation.

3. Combination with RDF, SPARQL, and Schema.org: The attributes of real-world and virtual elements are structured using the Schema.org vocabulary and serialized as RDF triples. A real-world business recognized in a scene is an RDF node of type schema:LocalBusiness with properties like schema:geo and schema:openingHours. The user's profile is also an RDF graph with schema:Person properties. The interference function is a set of SPARQL CONSTRUCT queries run against this combined graph. A query might construct a new "AR Offer" node only if a schema:Product's properties align with a schema:Person's interests and the schema:LocalBusiness is currently open, demonstrating a formal, semantic, and standardized method for calculating interference.