Obviousness

The current date is April 26, 2026.

Obviousness Analysis of US Patent 11671702 under 35 U.S.C. § 103

This analysis will identify combinations of prior art references that would render the claims of US Patent 11671702 obvious to a person having ordinary skill in the art (POSITA) and explain the motivation to combine them. A POSITA in this field would likely have a background in image processing, computer vision, and camera system design, understanding how various sensors and algorithms contribute to image quality.

The independent claims (Claim 1 and Claim 11) of US11671702 focus on combining multiple quality indicators (QIs) and confidence levels to provide real-time feedback and suggestions to a user to improve photo quality. The core inventive step, as described in the patent, lies in the dynamic adjustment of weights and consideration of confidence levels of QIs, allowing for more intelligent and context-aware picture quality assessment and feedback.

Combination 1: US 20130155474 in view of WO 2006040761/US20070195174

• US 20130155474 describes a system that provides user feedback prior to image capture, including instructions for adjusting measured parameters to improve image quality. It combines parameter values into an overall quality score that must exceed a threshold before an image can be captured. The publication explicitly states, "The user can be provided detailed information to assist the user in taking a better quality image of the document. For example, the blurriness may have been the result of motion blur caused by the user moving the camera while taking the image. The test result messages can suggest that the user hold the camera steadier when retaking the image." This directly addresses feedback and suggestions for improvement based on quality issues.

• WO 2006040761/US20070195174 discloses a system where an interface module defines scene dynamics (e.g., image motion speed, subject motion speed) and allows setting relative weights for captured image attributes in computing a total image grade.

Obviousness Argument for Claims 1 and 11:

A POSITA would find it obvious to combine the teachings of US 20130155474 and WO 2006040761/US20070195174 to arrive at the methods of Claims 1 and 11.

• Motivation to Combine: Both references address aspects of image quality assessment and user feedback. US 20130155474 provides the concept of giving feedback and suggestions based on quality parameters to improve a picture before it is taken. WO 2006040761/US20070195174 introduces the idea of using weights for different image attributes in computing a total image grade, specifically mentioning scene dynamics like image motion speed. A POSITA would be motivated to combine these to create a more sophisticated real-time feedback system. By integrating the weighted quality indicators from WO 2006040761/US20070195174 into the feedback mechanism of US 20130155474, the system could provide more nuanced and prioritized suggestions based on the relative importance of different quality factors and the specific scene conditions. For example, if device motion is a critical factor (as weighted by WO 2006040761/US20070195174), the feedback in US 20130155474 could specifically advise "hold the camera steadier."

• How the Combination Addresses Claim 1:

  • QI1 (Device Motion): WO 2006040761/US20070195174 explicitly mentions "image motion speed and motion speed of the subjects" and weights for computing a total image grade. This directly covers obtaining a value responsive to device motion.
  • QI2 (Exposure): While not explicitly detailed as a separate QI in the same way, US 20130155474 discusses "measured parameter" values being combined into an "overall quality score" before an image can be captured, implying various quality aspects, including exposure, would be considered. Exposure is a fundamental photographic parameter, and a POSITA would readily include it.
  • QI3 (Face Analysis): US 20130155474's general feedback mechanism could be extended to include face properties, as face detection and analysis were known in the art.
  • QI4 (Lens Obstruction): This is a specific quality indicator. While not explicitly taught in these references, the general concept of "measuring parameters" and giving feedback on how to improve an image in US 20130155474 would lead a POSITA to consider obvious impediments to image quality like lens obstruction, especially if such an obstruction impacted the overall quality score or parameter values.
  • Suggestions from pre-stored table: US 20130155474 clearly describes providing "detailed information to assist the user in taking a better quality image," including suggestions like "hold the camera steadier." This directly maps to selecting from a pre-stored table of suggestions.

• How the Combination Addresses Claim 11:

  • QI1 (Device Angle to Horizon): While not explicitly called "device angle to horizon," the "interface module further enables to define the scene dynamics of the captured image" in WO 2006040761/US20070195174 implies the capture of relevant camera orientation data that could be used to infer device angle. Combining this with the feedback system of US 20130155474, a POSITA would readily implement a quality indicator for device angle.
  • QI2 (Aesthetic Quality): The "captured image attributes relative weight for the computation of the total image grade" in WO 2006040761/US20070195174 can encompass aesthetic qualities. The subjective nature of "aesthetic quality" could be informed by rule-based systems or user preferences, and a POSITA would understand that different weights could be applied to such attributes.
  • Suggestions for improvement: Both references support providing suggestions to the user for improvement.

Combination 2: US 20090278958 in view of US 20130155474 and WO 2006040761/US20070195174

• US 20090278958 describes that "The scoring of a current base image may be based on scores which have been given to previously captured base images. In such a manner, redundant calculation may be avoided." This introduces the concept of using historical data (previous image scores) to inform the current image scoring.

Obviousness Argument for Claims 1 and 11 (with historical data):

A POSITA would be motivated to combine the teachings of US 20090278958 with the previous combination (US 20130155474 and WO 2006040761/US20070195174) to enhance the real-time quality assessment.

• Motivation to Combine: The combination of US 20130155474 and WO 2006040761/US20070195174 provides real-time feedback using weighted quality indicators. A POSITA would recognize that incorporating historical data, as taught by US 20090278958, could further refine the quality assessment and feedback process. Using previous image frames and their quality indicators (and confidence levels as introduced in US11671702) would lead to more stable and reliable quality assessments, especially in dynamic environments where single-frame analysis might be prone to errors or fluctuations. This would also enable the system to identify trends or persistent issues, leading to more intelligent and adaptive suggestions. For example, if the device consistently experiences shake in previous frames, the system might offer more persistent or emphatic "hold still" suggestions.

• How the Combination Addresses "previous image frames" and "confidence level":

  • US 20090278958 explicitly teaches using "scores which have been given to previously captured base images." This directly addresses the "previous image frames" aspect of US11671702's claims. While US 20090278958 focuses on avoiding redundant calculations, a POSITA would understand that this historical data could also be leveraged to assess the reliability or "confidence" of current readings. If a current quality indicator drastically deviates from a consistent trend in previous frames, the system could assign a lower confidence level to the current reading. The concept of "confidence level" for quality indicators, while explicitly detailed in US11671702, would be an obvious development for a POSITA seeking to improve the robustness and accuracy of a system that relies on multiple, potentially noisy, sensor inputs and image analyses over time.

General Motivation for a POSITA

Beyond specific combinations, a POSITA would have several general motivations to combine elements from the cited prior art:

• Improving User Experience: The primary goal of all cited prior art is to help users take better pictures. Combining various quality assessment techniques and feedback mechanisms would directly serve this goal.
• Leveraging Available Sensor Data: Modern devices (smartphones, for example) increasingly integrate multiple sensors (accelerometers, gyros, GPS, advanced camera modules). A POSITA would be motivated to utilize all available data to provide a comprehensive and accurate quality assessment, rather than relying on isolated indicators.
• Enhancing Real-Time Performance: The patent emphasizes "real-time assessment." Prior art already hints at this with feedback prior to capture. A POSITA would continuously seek to make these assessments faster and more responsive, which naturally leads to combining efficient algorithms and processing sensor data concurrently.
• Creating More Intelligent Systems: The shift from simple thresholds to weighted combinations and confidence levels reflects a general trend in computer vision and signal processing towards more intelligent, context-aware systems. A POSITA would strive to build a system that can understand not just what is wrong with a picture, but why it's wrong and how confident the system is in its assessment, leading to better suggestions.

The prior art collectively demonstrates that the individual components of US Patent 11671702, such as using multiple quality indicators, weighting them, providing real-time feedback, and considering historical data, were known in the art. The motivation to combine these elements to create a more comprehensive and intelligent real-time photo quality assessment and feedback system would be readily apparent to a person of ordinary skill in the art.