Video Background Segmentation and Alteration

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Users often forget to enable background effects in video conferences, leading to unintentional sharing of distracting, embarrassing, or confidential information due to background movement.

Innovation Solution

The system automatically applies mitigation actions, such as blurring or replacing the background, using machine learning for human segmentation and motion detection, allowing users to set sensitivity levels and customize the blur or replacement effects.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If background effects are automatically applied without user intervention, then user privacy and professionalism are enhanced, but device complexity and processing requirements increase

Engineering Contradiction:

Improveprivacy protectionVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs automatic background analysis and mitigation without requiring user intervention. The processor independently segments backgrounds, detects motion, and applies corrections, allowing the system to serve itself in protecting user privacy during video conferences.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-processes video frames by segmenting backgrounds before motion detection and correction. By performing background segmentation in advance using machine learning models, the system prepares the data structure needed for efficient motion detection and automated mitigation actions.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If motion detection sensitivity is increased to detect all background movements, then distracting information is better prevented, but false positives increase and may obscure legitimate background content

Engineering Contradiction:

Improvemotion detection accuracyVSAvoidfalse positive rate

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system applies different processing thresholds and analysis methods to different regions of the background. By segmenting the background into distinct areas and applying localized motion detection parameters, the system can maintain high sensitivity where needed while reducing false positives in other regions.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system dynamically adjusts motion detection parameters based on the analyzed background content. By changing sensitivity thresholds, detection windows, and correction criteria according to the specific scene being analyzed, the system optimizes the balance between detecting actual motion and avoiding false positives.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11798170B2Image background alterations

Publication Date: 2023.10.24 HEWLETT PACKARD DEVELOPMENT COMPANY LP

AI summary

Executable code causes a processor to segment a first frame to determine a background portion of the first frame, and segment a second frame to determine a background portion of the second frame. The executable code causes the processor to compare the background portion of the first frame to the background portion of the second frame to determine a difference between the first frame and the second frame. The executable code also causes the processor to alter the background portion of the second frame responsive to the difference. The executable code causes the processor to display the altered second frame on a display.