2D to 3D Image Conversion Depth Map Boundary Smoothing
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Solution Overview
Problem
Converting 2D images to 3D often introduces geometric distortions that cause discomfort, such as headaches and eye muscle pain, due to the strain on human viewing, particularly in consumer products.
Innovation Solution
The method involves segmenting a 2D image into regions with varying depths, generating a depth map that adjusts pixel depths based on distance from boundaries, and synthesizing left and right views to minimize geometric distortions by smoothing depth transitions and maintaining the foreground region's integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 2D image is converted to 3D image using conventional methods, then 3D visual effect is achieved, but geometric distortions are introduced causing viewing discomfort
Solution Approach 1:
The image is segmented into multiple depth regions (foreground, midground, background) with different depth values. This segmentation allows different regions to be warped differently during 3D conversion, preserving geometric integrity while maintaining 3D effect. The patent divides the image into at least three depth regions, where foreground pixels receive different warping treatment compared to background pixels, thereby reducing geometric distortions.
Solution Approach 2:
Different warping parameters are applied to different spatial regions of the image based on their depth classification. The patent applies local quality by using region-specific warping functions where foreground regions use one set of warping parameters and background regions use another, ensuring that each region maintains its geometric properties appropriately for its depth plane.
2Adaptability or versatility
If depth warping is applied to create 3D effect, then depth perception is enhanced, but geometric distortions increase causing strain on human viewing
Solution Approach 1:
The patent employs dynamic warping parameters that are adjusted based on the viewer's position and the specific depth region being processed. The warping function is not static but adapts to different spatial locations and depth planes, allowing optimal depth perception while minimizing geometric distortions that would cause viewing strain.
Solution Approach 2:
The patent changes warping parameters (such as horizontal displacement, vertical displacement, and scaling factors) based on the depth region and pixel location. By dynamically adjusting these parameters across different regions, the system enhances depth perception where needed while maintaining geometric accuracy in other areas, thereby improving viewing comfort.
3Device complexity
If uniform depth assignment is used for simplicity, then processing complexity is reduced, but geometric distortions occur at region boundaries
Solution Approach 1:
The patent performs preliminary classification of pixels into depth regions before the warping operation. By pre-segmenting the image into foreground, midground, and background regions and assigning appropriate depth values in advance, the system avoids complex real-time calculations during warping while maintaining geometric accuracy at region boundaries through the use of transition zones.
Solution Approach 2:
The patent introduces transition zones or intermediate regions at the boundaries between different depth regions. These intermediary zones use blended or interpolated depth values to smoothly connect adjacent regions, preventing abrupt geometric discontinuities at boundaries while maintaining processing efficiency through a structured multi-region approach.
Data Source
AI summary
For converting a two-dimensional visual image into a three-dimensional visual image, the two-dimensional visual image is segmented into regions, including a first region having a first depth and a second region having a second depth. The first and second regions are separated by at least one boundary. A depth map is generated that assigns variable depths to pixels of the second region in response to respective distances of the pixels from the boundary, so that the variable depths approach the first depth as the respective distances decrease, and so that the variable depths approach the second depth as the respective distances increase. In response to the depth map, left and right views of the three-dimensional visual image are synthesized.