Simulating Short Depth of Field for Videophone Privacy

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Solution Overview

Problem

Videophones with long depth of field capture all scene elements in focus, leading to privacy concerns as background details can be distracting and intrusive, with existing solutions either disabling video entirely or failing to prevent accidental capture of inappropriate content.

Innovation Solution

Implementing a simulated short depth of field by digitally segregating and blurring the background of the videophone image using image detection and processing techniques, such as convolution filters or fixed templates, to keep the foreground in focus while blurring the background, with user-selectable controls for customization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If long depth of field is used in videophone camera, then all scene elements from foreground to background are in focus providing sharp and clear overall image quality, but background details become distracting and privacy is compromised

Engineering Contradiction:
Improveimage sharpnessVSAvoidprivacy intrusion
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent segments the video image into foreground and background portions, applying different focus treatments to each segment. The foreground containing the user is kept in focus while the background is blurred, thereby maintaining image quality for the subject while protecting privacy by obscuring sensitive background details.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by selectively blurring only the background portions of the image while keeping the foreground sharp. This allows different regions of the same image to have different focus characteristics, preserving the sharpness needed for the user while introducing blur in the background to protect privacy.

Inventive Principle:
Principle #3Local quality

2Object-affected harmful factors

If user controls are added to disable video camera for privacy, then privacy is protected by preventing background capture, but the video function is completely lost removing a primary videophone feature

Engineering Contradiction:
Improveprivacy protectionVSAvoidvideo function availability
Core Design Contradiction:
Object-affected harmful factorsVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamic background blurring that automatically adjusts based on the detected foreground subject position and movement. The system continuously tracks the user and adapts the blur regions accordingly, providing privacy protection that is active only when needed rather than a static disabled state, thus preserving video functionality while protecting privacy.

Inventive Principle:
Principle #15Dynamics

3Object-affected harmful factors

If digital image processing techniques are used to blur background, then privacy is enhanced while preserving video function, but processing complexity and computational requirements increase

Engineering Contradiction:
Improveprivacy enhancementVSAvoidprocessing complexity
Core Design Contradiction:
Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The patent segments the image processing task into distinct steps: foreground detection, background identification, and selective blurring application. This segmentation of the processing workflow makes the complex task more manageable and allows for optimization at each stage, reducing overall computational complexity while achieving privacy protection.

Inventive Principle:
Principle #1Segmentation

Data Source

PatentUS7911513B2Simulating short depth of field to maximize privacy in videotelephony
Publication Date: 2011.03.22 GOOGLE TECHNOLOGY HOLDINGS LLC
  • US7911513B2 patent drawing
  • US7911513B2 patent drawing
  • US7911513B2 patent drawing

AI summary

An arrangement for simulating a short depth of field in a captured videophone image is provided in which the background portion of the image is digitally segregated and blurred to render it indistinct. Thus, the displayed video of a user in the foreground is kept in focus while the background appears to be out of focus. Image tracking or fixed templates are used to segregate an area of interest that is kept in focus from the remaining captured video image. Image processing techniques are applied to groups of pixels in the remaining portion to blur that portion of the captured video image. Such techniques include the application of a filter that are alternatively selected from convolution filters in the spatial domain (e.g., mean, median, or Gaussian filters), or frequency filters in the frequency domain (e.g., low-pass or Gaussian filters). User-selectable control is optionally implemented for controlling the type of foreground/background segregation technique utilized (i.e., dynamic face-tracking or fixed template shape), degree of blurring applied to the background, and on/off control of the background blurring.