3D Model-Guided Background Updates for Motionless Foreground Extraction
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Solution Overview
Problem
Existing foreground extraction methods face challenges in accurately updating background images due to objects being motionless or timing issues, leading to inaccurate foreground region extraction.
Innovation Solution
An image processing apparatus that utilizes a three-dimensional model to determine the presence of a target object in input images and updates the background image accordingly, ensuring precise foreground/background separation even when the object is motionless.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the predetermined period for updating the background image is short, then the updating frequency is high, but the background image is updated incorrectly when the object is motionless, reducing extraction accuracy
Solution Approach 1:
The patent introduces a three-dimensional model as an intermediary between the input image and the background image update process. The 3D model, generated from foreground extraction results, serves as a mediator to determine whether background updates should occur. This intermediary layer prevents direct updates when objects are motionless by providing spatial and temporal context about object presence and movement, thereby resolving the contradiction between update frequency and extraction accuracy.
Solution Approach 2:
The patent transitions from two-dimensional image processing to three-dimensional modeling by generating 3D models from foreground regions. This dimensional change allows the system to track object presence and motion in a more robust manner, enabling accurate determination of whether background updates are appropriate even when objects appear stationary in 2D images. The 3D dimension provides additional information about object depth, volume, and motion that resolves the accuracy-frequency trade-off.
2Reliability
If the predetermined period for updating the background image is long, then the updating frequency is low, but the background image is not updated at suitable timing, reducing extraction accuracy
Solution Approach 1:
The patent implements a feedback mechanism where the three-dimensional model continuously monitors object presence and motion states, and this information feeds back to control the background image update timing. The system only updates the background image when the 3D model indicates that objects have moved or disappeared, ensuring updates occur at suitable timing rather than at fixed intervals. This feedback loop resolves the contradiction by making update reliability dependent on actual scene changes rather than predetermined periods.
Solution Approach 2:
The patent transforms the static, fixed-interval background update approach into a dynamic, condition-based update system. Instead of updating at predetermined periods regardless of scene content, the system dynamically adjusts update timing based on real-time analysis of the three-dimensional model and object motion states. This dynamic approach ensures background images are updated at optimal moments when objects have actually moved, resolving the contradiction between update reliability and extraction accuracy.
3Device complexity
If background subtraction is used for foreground extraction, then the method is simple, but accurate extraction requires a high-precision background image which is difficult to maintain
Solution Approach 1:
The patent applies preliminary action by generating and maintaining a three-dimensional model of objects in advance of the background update decision. This 3D model is created from foreground extraction results and prepared beforehand to serve as a reference for determining whether background updates are needed. By having this preliminary 3D representation ready, the system can make informed update decisions without requiring complex real-time analysis, thus maintaining simplicity while improving accuracy.
Data Source
AI summary
A background image is suitably updated even in a case where a target object is motionless. An image processing apparatus according to the present disclosure obtains data on an input image, data on a background image used to extract a foreground region from the input image, and data on a three-dimensional model generated based on the foreground region extracted from the input image, and updates the background image based on the input image and the three-dimensional model.