2D Image Depth and Volume Conversion via Pixel Offsets
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Solution Overview
Problem
Current methods for converting 2D multimedia content to 3D or stereoscopic content are labor-intensive and require specialized skills, as they involve creating virtual 3D environments and models, which is time-consuming and requires significant manual labor, especially when dealing with animated objects and complex scenes.
Innovation Solution
The method involves extracting layers from a 2D image, applying pixel offsets to create depth and volume effects by generating corresponding left and right eye images with adjusted pixel positions, using techniques such as gray scale templates and gradient modeling to provide a stereoscopic 3D effect without the need for extensive virtual 3D modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If virtual 3D environments and models are created to convert 2D content to 3D, then stereoscopic 3D effect quality is improved, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent uses projection mapping to copy 2D color information from the original image onto 3D virtual models. Instead of manually recreating every element in 3D, the system automatically projects and maps the 2D image data onto 3D models, significantly reducing manual labor while maintaining visual fidelity. This copying approach allows the 2D image information to be transferred to the 3D space efficiently.
Solution Approach 2:
The patent replaces manual mechanical work (artists manually positioning and animating 3D models frame by frame) with automated computational processes. The system automatically performs projection mapping, model positioning, and animation synchronization using algorithms that process the 2D image data and generate corresponding 3D stereoscopic output without requiring frame-by-frame manual intervention.
2Manufacturing precision
If virtual models are precisely tracked and altered frame by frame to match 2D image movement, then animation accuracy is improved, but time consumption and manual labor increase
Solution Approach 1:
The system implements automatic tracking and animation synchronization where the projection mapping algorithm automatically adjusts the 3D virtual models to match the movement and deformation in the 2D source image. The process is self-service in the sense that the system autonomously performs the tracking and adjustment without requiring continuous manual intervention for each frame, reducing time consumption while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary setup by creating the 3D virtual models and establishing the projection mapping parameters before the actual conversion process. This preliminary action includes defining the camera positions, lighting, and model structures in advance, so that during the actual frame-by-frame conversion, only the positioning and color projection need to be adjusted automatically, significantly reducing the time required for each frame.
3Manufacturing precision
If the entire 2D image is recreated in a virtual 3D environment, then complete depth and volume control is improved, but device complexity and manual labor requirements increase
Solution Approach 1:
The patent segments the conversion process into distinct components: 2D image analysis, 3D virtual model creation, projection mapping, and stereoscopic rendering. By dividing the complex task of complete image recreation into these manageable segments, the system can apply specialized algorithms to each part, reducing overall system complexity while maintaining comprehensive depth and volume control capability.
Solution Approach 2:
The projection mapping system serves multiple functions simultaneously: it transfers color information from 2D to 3D, positions objects in depth space, controls volume appearance, and generates both left and right eye views for stereoscopic display. This multi-functionality reduces the need for separate specialized tools and processes, simplifying the overall system while achieving complete depth and volume control.
Data Source
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AI summary
Implementations of the present disclosure involve methods and systems for creating depth and volume in a 2-D image by utilizing a plurality of layers of the 2-D image, where each layer comprises one or more portions of the 2-D image. Each layer may be reproduced into a corresponding left eye and right eye layers that include a depth pixel offset corresponding to a perceived depth. Further, a volume effect may also be applied to one or more objects of the 2-D image by associating a volume pixel offset to one or more pixels of the image. Thus, any pixel of the 2-D image may have a depth pixel offset to provide a perceived depth as well as a volume pixel offset to provide a stereoscopic 3-D volume effect. In this manner, the 2-D image may be converted to a corresponding stereoscopic 3-D image with perceived depth and volume effects applied.