US 10944901

US Patent 10944901, titled "Real time assessment of picture quality," was filed on May 6, 2020, and issued on March 9, 2021. The current and original assignee is Snapaid Ltd., and the inventor is Ishay Sivan.

Abstract:
The patent describes a computerized method for evaluating the photo quality of a captured image within a device's image acquisition system. This method involves combining multiple quality indicators (QIs) computed from the current and previous image frames, along with a confidence level for at least one of these QIs. A processor then uses this combined information to determine if the photo quality is acceptable and takes different actions based on whether the quality meets the acceptable criteria.

Independent Claims Overview:

• Claim 1 (Method for computing photo quality): This claim describes a method that involves:

  1. Computing Quality Indicators: Calculating at least two different quality indicators (QIs) for a captured image, using data from the current image and previous image frames. This computation also includes determining a confidence level for at least one of these QIs.
  2. Combining and Determining Acceptability: Combining these QIs to create at least one "total quality indicator." This total indicator is then used to decide if the overall photo quality is acceptable.
  3. Taking Differential Action: Based on whether the photo quality is acceptable or not, the system takes a specific, different action.
  4. Providing Feedback: The system provides detailed feedback about the photo quality.
  5. Adjusting Parameters: The computed QIs and their confidence levels are used to modify parameters within the lens/sensor module to improve the total quality indicator.
  6. Automatic Capture: The capturing device is automatically activated when a logical criterion, based on the QIs, is met.

• Claim 16 (System for real-time picture quality assessment): This claim outlines a system designed to assess picture quality in real time on a device with multiple sensors. The system comprises:

  1. Multiple Sensors: The device includes various sensors, such as an image sensor, accelerometer, or gyroscope, which provide data.
  2. Processing Component: A processing component receives data from these sensors and computes multiple quality indicators (QIs) and their confidence levels. It also combines these QIs to create a total quality indicator.
  3. Decision-Making: The processing component uses the total quality indicator to determine if a picture's quality is acceptable.
  4. Action Initiation: Based on the quality assessment, the processing component initiates an action, such as providing feedback to the user or adjusting camera parameters.
  5. Data Saving: The system saves quality indicators along with the image.

• Claim 17 (Computer program product): This claim describes a computer program product that includes a non-transitory computer-readable storage medium. This medium stores computer program code designed to be executed by a computer to implement a method for computing photo quality. The method performed by this program code is identical to the steps outlined in Claim 1.

CAFC 2026 Dockets:
As of April 26, 2026, a search of CAFC 2026 dockets for patent number 10944901 did not yield any specific results in the provided snippets. The search results contained general information about CAFC activity and USPTO search tools, but no direct mention of litigation or appeals involving this particular patent number within the specified timeframe.

As a patent attorney, I have investigated litigation records for US Patent 10944901.

Based on the available information as of April 26, 2026, the following litigation is known:

• Jurisdiction: Texas Eastern District Court
  • Case Number: 2:25-cv-00378
  • Plaintiff(s): Not specified in the provided information, but the source is "District Court".
  • Defendant(s): Not specified in the provided information.
  • Filing Date: Not explicitly stated in the provided snippet, but the case is listed under "US case filed in Texas Eastern District Court".
  • Outcome/Current Status: Litigation is active.

Additionally, a PTAB (Patent Trial and Appeal Board) case has been filed:

• Jurisdiction: PTAB
  • Case Number: IPR2025-01519
  • Petitioner: Unified Patents PTAB Data
  • Filing Date: Not explicitly stated in the provided snippet, but the case is listed.
  • Outcome/Current Status: Not Instituted - Procedural.

Finally, there is also a record of the "First worldwide family litigation filed" for this patent family.

• Jurisdiction: Global (Darts-ip)
  • Case Number: Not specified in the provided information.
  • Plaintiff(s): Not specified in the provided information.
  • Defendant(s): Not specified in the provided information.
  • Filing Date: Not specified in the provided information.
  • Outcome/Current Status: Litigation.

Proceedings overview

There is currently one AIA trial proceeding on file for US Patent 10,944,901. The petition was denied institution, specifically via a discretionary denial. This means all claims of the patent remain untested by the PTAB through this proceeding, offering little direct impact on the defensive posture of a defendant, other than indicating the PTAB chose not to review the merits of the petition.

IPR2025-01519 — [[[Samsung Electronics Co.](/litigations/by-defendant/Samsung%20Electronics%20Co.), Ltd.](/litigations/by-plaintiff/Samsung%20Electronics%20Co.%2C%20Ltd.) et al.](/litigations/by-plaintiff/Samsung%20Electronics%20Co.%2C%20Ltd.%20et%20al.) v. Snapaid Ltd.

• Type: Inter Partes Review
• Filed: 2025-09-05
• Status: Discretionary Denial. The PTAB declined to institute the IPR.
• Judge panel: Undisclosed from public search results.
• Petition grounds: The specific claims challenged, prior art asserted, and statutory bases (§ 102 / § 103 / § 112) are not publicly detailed in the denial status itself, and would typically be found in the petition and institution decision, which was not issued on the merits.
• Institution decision: Denied. The PTAB issued a Discretionary Denial on 2026-03-11. The reasoning for a discretionary denial often relates to factors like parallel district court litigation, advanced stage of litigation, or inefficient use of Board resources, rather than the merits of the patentability challenge. Specific details of the reasoning are not immediately available without access to the full decision.
• Final Written Decision: Not applicable, as institution was denied.
• Settlement / termination: Not applicable, as the proceeding was terminated by a discretionary denial of institution.
• Appeal: No appeal of the discretionary denial has been publicly reported.
• Defensive value: As the IPR was denied institution on discretionary grounds, no claims were reviewed on the merits by the PTAB. This means the patent's claims retain their full presumption of validity, and no estoppel applies to the petitioner (or its privies) under 35 U.S.C. § 315(e)(2) for grounds that were raised or reasonably could have been raised in this IPR. A defendant facing assertion of this patent will need to develop their own invalidity contentions, as this IPR did not result in any claim cancellation.

Strategic summary

All claims of US Patent 10,944,901 remain UNTESTED by the PTAB through the IPR2025-01519 proceeding due to a discretionary denial of institution. No claims were canceled, and no claims were sustained as patentable by a Final Written Decision. This means the patent's claims are considered to have their full presumption of validity from the USPTO, as no challenge to their validity has been adjudicated by the PTAB.

The estoppel landscape for this patent is clear: since IPR2025-01519 was denied institution, neither Samsung Electronics Co., Ltd. et al. nor their privies are subject to the estoppel provisions of 35 U.S.C. § 315(e)(2). This leaves all prior-art grounds potentially available for future challenges or defenses, assuming other estoppel events (e.g., in district court litigation) are not applicable.

Regarding pattern signals, only one IPR has been filed against US Patent 10,944,901 to date. The petitioner was Samsung Electronics Co., Ltd. et al. The fact that the proceeding resulted in a discretionary denial, rather than a merits-based institution or denial, suggests that the PTAB considered factors external to the patentability arguments themselves (e.g., related litigation, stage of district court proceedings) when making its decision. While Google Patents lists Unified Patents as a petitioner in IPR2025-01519, the structured "PTAB proceedings on file" block in the prompt, which is designated as the canonical ground truth, states the petitioner as "Samsung Electronics Co., Ltd. et al.".

Recommended next steps

• Since IPR2025-01519 was denied institution, there is no Final Written Decision to cite for claim invalidation. All claims of US 10,944,901 remain intact from a PTAB perspective.
• For a defendant, the absence of an instituted IPR means the claims have not been subjected to PTAB scrutiny. Any defensive strategy should involve a thorough prior art search and analysis to identify strong invalidity grounds, as if no PTAB proceedings had occurred.
• While the discretionary denial is public, accessing the full decision on the USPTO PTAB E2E system (https://ptab.uspto.gov/#/login) would be beneficial to understand the Board's precise reasoning for the denial. This information could be crucial in assessing the likelihood of success for any future PTAB petitions against this patent, especially if they involve similar timing or litigation postures.

https://portal.unifiedpatents.com/ptab/case/IPR2025-01519

Inventors

• Ishay Sivan (Snapaid Ltd.)

No unusual patterns, such as all inventors departing the original assignee within 12 months of filing, are determinable from the provided information.

Original assignee

The original assignee is Snapaid Ltd. Snapaid Ltd. does not appear to ship a product embodying the claims of US 10944901; instead, its primary line of business is patent licensing and assertion. Litigation documents state that "SnapAid has no apparent business operations other than asserting its patent portfolio". The company's website also explicitly invites inquiries for "IP and technology for licensing" and to "See our patent portfolio". Snapaid Ltd. is currently operating as a patent asserting entity, as evidenced by its active litigation against Samsung.

Assignment timeline

• 2020-05-06 (executed) / recorded 2020-05-06 — Reel 054817/0116
  • Conveyance: ASSIGNMENT OF ASSIGNORS INTEREST
  • Assignor: SIVAN, Ishay
  • Assignee: SNAPAID LTD.
  • Correspondent: NOT LISTED
  • Context: Initial assignment from inventor to the filing entity.

The USPTO Patent Assignment Search for US10944901 shows only one recorded assignment from the inventor to Snapaid Ltd.

Timeline diagram

timeline
    title Ownership of US 10944901
    2020 : Filed, inventor assigned to Snapaid Ltd
    2021 : Issued
    2025 : First infringement suit filed

NPE / troll-pattern signals

1. Shell-entity transfer — Present. While the initial transfer was from the inventor, Snapaid Ltd. itself functions as a licensing-only entity. Litigation documents state that "SnapAid has no apparent business operations other than asserting its patent portfolio". Furthermore, the SnapAid website openly solicits inquiries for "IP and technology for licensing". This indicates Snapaid Ltd. operates as a shell entity for patent assertion.
2. Known asserter in the chain — Present. Snapaid Ltd. is actively asserting US 10944901 against [Samsung Electronics Co., Ltd.](/litigations/by-plaintiff/Samsung%20Electronics%20Co.%2C%20Ltd.) and Samsung Electronics America, Inc. in the Eastern District of Texas (Case No. 2:25-cv-00378).
3. Repeat correspondent across the chain — Not present. The single recorded assignment (Reel 054817/0116) does not list a correspondent.
4. Cascading transfers — Not present. There is only one recorded assignment in the chain from the inventor to Snapaid Ltd.
5. Pre-litigation transfer — Not present. The assignment from Ishay Sivan to Snapaid Ltd. was executed and recorded on 2020-05-06 (Reel 054817/0116). The litigation against Samsung was filed on April 10, 2025, which is more than six months after the assignment.
6. Bankruptcy fire-sale — Not present. No evidence of bankruptcy proceedings or fire-sale related transfers.
7. Privateering — Unclear. The patent was assigned directly from the inventor to Snapaid Ltd. There is no public information indicating that an operating company transferred the patent to Snapaid Ltd. to assert on its behalf.
8. Defensive aggregator (anti-NPE) — Not present. The patent is currently being asserted by Snapaid Ltd., not held by a defensive aggregator.

Verdict

NPE — high confidence

The high confidence in Snapaid Ltd. being an NPE is supported by two strong signals: Snapaid Ltd. acts as a shell entity whose "business operations other than asserting its patent portfolio" are non-existent. Additionally, Snapaid Ltd. is a known asserter, currently litigating this patent against Samsung in the Eastern District of Texas (Case No. 2:25-cv-00378).

For verification, see the USPTO Assignment Center search for US10944901: https://assignmentcenter.uspto.gov/

To identify the most relevant prior art for US patent 10944901, I will examine the patent citations listed in the patent document itself. The patent mentions several prior art documents in its "BACKGROUND" section. I will then provide the requested details for each.

Here's an analysis of the prior art cited in US10944901:

Prior Art References and Analysis:

1. US 2013/0155474 A1

   • Full Citation: US 2013/0155474 A1 to Silverstein et al.
   • Publication/Filing Date: Publication date: June 20, 2013. The corresponding application, U.S. application Ser. No. 13/328,007, was filed on December 16, 2011.
   • Brief Description: This patent describes providing feedback to a user of a mobile device prior to capturing an image, specifically of a paper document. The feedback includes instructions for adjusting measured parameters. Parameter values can be combined into a group threshold or overall quality score, and the image is only captured if this score exceeds a defined threshold. It explicitly mentions suggesting the user hold the camera steadier if blurriness is detected due to motion.
   • Potential Anticipated Claims (under 35 U.S.C. § 102):
     • Claim 1: This reference appears to anticipate several elements of Claim 1, particularly the computing of quality indicators, combining them into a total quality score to determine acceptability, and taking differential action (capturing the image only if the threshold is met). The feedback mechanism ("instructions for adjusting at least one measured parameter" and "suggest that the user hold the camera steadier") also aligns with providing detailed photo quality feedback. The concept of using quality indicators to control the capturing apparatus (by enabling/disabling capture based on a threshold) is present.
     • Claim 16: The system described would involve sensors (to measure parameters), a processing component (to combine parameter values into a quality score), decision-making (determining if quality is acceptable based on the score), and action initiation (capturing the image or providing feedback).
     • Claim 17: As it describes a method, it would inherently be implementable by a computer program product.

2. WO 2006/040761 A1 / US 2007/0195174 A1

   • Full Citation: WO 2006/040761 A1 (published April 20, 2006) and US 2007/0195174 A1 (published August 23, 2007) by Gotsman et al.
   • Publication/Filing Date: WO 2006/040761 A1: publication date April 20, 2006. US 2007/0195174 A1: publication date August 23, 2007, filed February 16, 2006.
   • Brief Description: These documents describe a system where an interface module defines scene dynamics (e.g., image motion speed, subject motion speed) and allows setting relative weights for these attributes in computing a total image grade.
   • Potential Anticipated Claims (under 35 U.S.C. § 102):
     • Claim 1: The concept of computing multiple quality indicators (scene dynamics like motion speed), combining them into a total quality indicator ("total image grade"), and allowing for adjustable weights is directly anticipated.
     • Claim 16: A system that processes image data to determine scene dynamics and applies weights to compute a grade would be relevant.

3. US 2009/0278958 A1

   • Full Citation: US 2009/0278958 A1 to Katayama et al.
   • Publication/Filing Date: Publication date: November 12, 2009. The corresponding application, U.S. application Ser. No. 12/460,917, was filed on July 23, 2009.
   • Brief Description: This patent describes scoring a current base image based on scores given to previously captured base images to avoid redundant calculations.
   • Potential Anticipated Claims (under 35 U.S.C. § 102):
     • Claim 1: The use of "previous image frames" data in computing quality indicators is directly addressed.
     • Claim 16: A system that utilizes previously captured image data for scoring is relevant.

4. U.S. Pat. No. 7,362,354

   • Full Citation: U.S. Pat. No. 7,362,354 to Silverstein et al.
   • Publication/Filing Date: Granted April 22, 2008. Filed January 18, 2005.
   • Brief Description: While the full text is not provided in the prompt, this patent is cited in the "BACKGROUND" section of US10944901 as conventional technology. Without further details on its specific teachings, a definitive statement about its anticipatory nature is difficult. However, given the context of US10944901, it is likely related to image quality assessment or feedback systems.

5. WO 2003/069559 A1

   • Full Citation: WO 2003/069559 A1 to Gotsman et al.
   • Publication/Filing Date: Published August 21, 2003.
   • Brief Description: Similar to US 7,362,354, the full text is not provided. As a cited reference in the "BACKGROUND", it likely deals with aspects of image processing or quality assessment.

6. U.S. Pat. No. 7,688,379

   • Full Citation: U.S. Pat. No. 7,688,379 to Ben-Ezra et al.
   • Publication/Filing Date: Granted March 30, 2010. Filed September 2, 2005.
   • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

7. US 2009/0263028 A1

   • Full Citation: US 2009/0263028 A1 to Kawakita et al.
   • Publication/Filing Date: Published October 22, 2009. Filed April 14, 2009.
   • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

8. US 2006/0017820 A1

   • Full Citation: US 2006/0017820 A1 to Kageyama et al.
   • Publication/Filing Date: Published January 26, 2006. Filed July 21, 2005.
   • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

9. US 2006/0056835 A1

   • Full Citation: US 2006/0056835 A1 to Funaya.
   • Publication/Filing Date: Published March 16, 2006. Filed September 14, 2005.
   • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

10. U.S. Pat. No. 8,125,557

    • Full Citation: U.S. Pat. No. 8,125,557 to Gotsman et al.
    • Publication/Filing Date: Granted February 28, 2012. Filed May 28, 2008.
    • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

11. WO 2011/148212 A2

    • Full Citation: WO 2011/148212 A2 to Liu et al.
    • Publication/Filing Date: Published December 1, 2011.
    • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

12. U.S. Pat. No. 7,920,727

    • Full Citation: U.S. Pat. No. 7,920,727 to Gotsman et al.
    • Publication/Filing Date: Granted April 5, 2011. Filed September 28, 2007.
    • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

13. U.S. Pat. No. 8,040,382

    • Full Citation: U.S. Pat. No. 8,040,382 to Gotsman et al.
    • Publication/Filing Date: Granted October 18, 2011. Filed March 1, 2010.
    • Brief Description: No full text provided. Cited in "BACKGROUND". Likely relates to image quality assessment.

Summary of Anticipation:

Based on the descriptions provided in US10944901's "BACKGROUND" section, the prior art references US 2013/0155474 A1, WO 2006/040761 A1 / US 2007/0195174 A1, and US 2009/0278958 A1 appear to be highly relevant and potentially anticipate various aspects of claims 1, 16, and 17 of US10944901.

• US 2013/0155474 A1 broadly anticipates the core concept of computing quality indicators, combining them for acceptability, taking differential action (like automatic capture based on a threshold), and providing feedback to improve image quality.
• WO 2006/040761 A1 / US 2007/0195174 A1 specifically anticipate the use of multiple QIs, combining them into a total grade, and utilizing adjustable weights, which are key features of US10944901's approach to combining QIs.
• US 2009/0278958 A1 directly addresses the use of "previously captured base images" for scoring, which is a component of Claim 1 ("previous image frames").

For the other listed patents (U.S. Pat. No. 7,362,354; WO2003069559; U.S. Pat. No. 7,688,379; US20090263028; US20060017820; US20060056835; U.S. Pat. No. 8,125,557; WO2011148212; U.S. Pat. No. 7,920,727; US20130155474; U.S. Pat. No. 8,040,382), without access to their full text or more detailed summaries, a precise determination of their anticipatory scope against specific claims of US10944901 is not possible. However, as they are cited as "conventional technology constituting background to certain embodiments of the present invention," it can be inferred that they disclose elements related to image processing and quality assessment that form the general field of the invention.

Obviousness Analysis under 35 U.S.C. § 103 for US Patent 10,944,901

This analysis evaluates the obviousness of US Patent 10,944,901 ("the '901 patent") by identifying combinations of prior art references that would render the claimed invention obvious to a person having ordinary skill in the art (POSITA).

1. Closest Prior Art References

The '901 patent itself identifies several relevant prior art documents in its "BACKGROUND" section. For this analysis, we will focus on the following key references:

• US 2013/0155474 A1 (Sargent et al.): This reference discloses a system that provides feedback to a user prior to image capture, combines measured parameter values into an overall quality score, and captures an image only if this score exceeds a defined threshold. It also provides detailed instructions for the user to adjust parameters to achieve a better quality image, for instance, suggesting the user hold the camera steadier to address motion blur. [cite: a]
• WO 2006/040761 A1 / US 2007/0195174 A1 (Elbaz et al.): This reference describes a system where an interface module enables defining scene dynamics, including image motion speed, and allows setting relative weights for captured image attributes in the computation of a total image grade. [cite: b]
• US 2009/0278958 A1 (Choi et al.): This reference teaches that the scoring of a current image can be based on scores given to previously captured base images to avoid redundant calculations. [cite: c]

2. Differences Between the Claims of US 10,944,901 and the Closest Prior Art

The independent claims of the '901 patent (Claims 1, 16, and 17) introduce several features not explicitly present or combined in an obvious manner in the identified prior art:

• Confidence Level for Quality Indicators (QIs): The '901 patent explicitly claims computing "a confidence level for at least one of said quality indicators" (Claim 1) and utilizing these confidence levels in the overall system (Claim 16). The patent explains that prior art computed QIs "without taking into account the possibility of error in the computed QI, as all sensors give out errors," and that a "confidence level" is obtained to address unreliable or fluctuating QI values.
• Dynamic and Inter-Dependent Weighting of QIs: The '901 patent highlights that "the weight of one indicator will take into account data from other quality indicator/s e.g. their quality indicator value, weight, confidence level... and their previous value, weight and confidence level." This is contrasted with prior art that uses "constant or can be change by the user manually" weights. [cite: b] A key example provided is disregarding an aesthetic quality indicator if device shake or camera focus QIs indicate poor quality, even if the user prioritized aesthetics, to prevent blurry pictures.
• Automatic Adjustment of Lens/Sensor Module Parameters: Claim 1 specifies "adjusting parameters in the lens/sensor module to achieve better total QI." While Sargent et al. provides suggestions to the user for adjustment [cite: a], it does not teach automatic, system-initiated adjustment of camera hardware parameters (e.g., ISO, aperture, shutter speed, focus point) based on computed QIs and confidence levels.

3. Motivation to Combine Prior Art References

A POSITA, typically an engineer or scientist skilled in image processing, computational photography, or embedded systems for cameras, would aim to develop more robust, accurate, and user-friendly real-time photo quality assessment systems.

Combination of Sargent et al. and Choi et al.

• Motivation: To improve the reliability and temporal consistency of real-time image quality assessment. Sargent et al. provides a real-time system that assesses quality and provides feedback/takes action on a current frame. [cite: a] Choi et al. teaches using scores from previously captured images for current scoring to avoid redundant calculations. [cite: c] A POSITA would be motivated to combine these to enhance the quality assessment by considering not just the current frame but also historical data, thereby stabilizing the quality metric against transient fluctuations and producing a more reliable assessment over time. This would lead to a more effective real-time system that better assists users in capturing good images.

Adding Elbaz et al.

• Motivation: To allow for more flexible and context-aware determination of total image quality. Elbaz et al. teaches setting relative weights for different image attributes in computing a total image grade. [cite: b] A POSITA, having combined Sargent et al. and Choi et al. for a more stable quality assessment, would find it obvious to incorporate dynamic weighting (as taught by Elbaz et al.) to adapt the overall quality score to different scene conditions or user preferences, thereby making the system more versatile and intelligent.

Addressing Automatic Adjustment of Lens/Sensor Module Parameters

• Motivation: To enhance the automation and responsiveness of the image acquisition system. Sargent et al. provides detailed feedback to the user on how to improve an image (e.g., "hold the camera steadier"). [cite: a] Given the trend towards greater automation in modern camera systems (even at the priority date of 2012-10-23), a POSITA would be motivated to replace these user instructions with automatic adjustments of the lens/sensor module parameters (e.g., shutter speed, ISO, aperture, focus) to directly correct detected quality issues. This would improve the user experience by reducing manual intervention and enabling faster, more precise corrections in real time. For example, if the system detects excessive device shake (a parameter measured by Sargent et al. [cite: a]), it would be an obvious engineering solution to automatically increase ISO or change aperture to allow a faster shutter speed, rather than merely telling the user to "hold still." The patent also mentions using quality indications to control the lens module, for instance, shortening shutter speed if movement is detected perpendicular to the focus plane.

Addressing Confidence Levels and Inter-Dependent Dynamic Weighting

This is the most challenging aspect to render obvious. While general knowledge recognizes that sensor data and algorithmic outputs have errors, the explicit and detailed mechanism for:

1. Computing a specific "confidence level" (C_i(t)) for each individual quality indicator (e.g., using a probability factor P_i(t) and a normal distribution N(x) as shown in the patent's formula C_i(t) = P_i(t_j2) * N(P_i(t_j2))).
2. Using these confidence levels to dynamically adjust the overall QI value (QI_ForTotal(t)i = QI(t)i * Π f_ij(t, QI(t)j, Cj)).
3. Applying a weighting scheme (w(t, Ci)i) where the weight of one indicator explicitly "take[s] into account data from other quality indicator/s e.g. their quality indicator value, weight, confidence level... and their previous value, weight and confidence level." [cite: b]

None of the cited prior art references (Sargent et al., Elbaz et al., Choi et al.) explicitly teach this sophisticated, multi-factor, inter-dependent dynamic weighting scheme based on individually computed confidence levels for each QI. While Elbaz et al. mentions relative weights [cite: b], it does not suggest that the weight of an aesthetic QI should be disregarded if a blur QI indicates poor quality with high confidence, as specifically exemplified in the '901 patent. This conditional, confidence-aware weighting represents a significant step beyond merely assigning static or simple dynamic weights. The motivation to implement such a complex system would be to overcome the problem of prior art systems taking blurry pictures despite user preferences, by prioritizing fundamental quality issues over secondary ones when confidence in the fundamental issue is high. However, arriving at this specific solution without the explicit teaching would likely require more than routine experimentation or common sense from a POSITA.

4. Conclusion

The combination of Sargent et al., Choi et al., and Elbaz et al. would render obvious many aspects of the '901 patent's claims, including:

• Computing a total quality indicator from multiple QIs, including data from previous frames.
• Determining acceptability based on this total QI.
• Taking differential action (e.g., capturing the image or providing feedback).
• Providing detailed feedback to the user.
• Automatically adjusting camera parameters (e.g., ISO, shutter speed, aperture) in response to detected quality issues.

However, the specific methods for:

1. Explicitly computing a "confidence level" for each individual quality indicator, using detailed formulas involving probability factors and statistical distributions.
2. Dynamically adjusting the weight of one quality indicator based on the values and confidence levels of other quality indicators (and their previous states), particularly to conditionally disregard certain QIs (like aesthetic QIs when a fundamental flaw like shake or focus is present and highly confident).

These two features, as detailed in the '901 patent, represent a more sophisticated and intelligent approach to real-time quality assessment than what is explicitly taught or rendered obvious by the combination of the cited prior art. The patent itself highlights these as key differentiating aspects over prior art's limitations. Therefore, while many elements might be obvious, the specific, inter-dependent, and confidence-level-driven dynamic weighting scheme for quality indicators, particularly its explicit formulation and application, may present a stronger argument against obviousness.