2D to 3D Image Conversion via Depth Map Generation
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Solution Overview
Problem
Users are limited in their ability to access a wide range of 3D video content due to the lack of conversion methods for existing 2D video content, requiring users to wait for graphic content providers to convert 2D content into 3D.
Innovation Solution
A method and device that analyze 2D images to generate depth maps, converting 2D images into 3D by creating left-eye and right-eye images using global and local depth information, allowing for the generation of 3D images from existing 2D content without additional equipment or modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 2D video contents are converted to 3D video contents by graphic content providers, then the quality and availability of 3D content is improved, but the time required for users to access 3D content increases and the complexity of the conversion process increases
Solution Approach 1:
The patent enables users to convert 2D video content to 3D content themselves using a portable terminal device, eliminating the need to wait for graphic content providers. The terminal analyzes the 2D video, generates depth information, and creates 3D content locally, allowing immediate access without external service dependency.
Solution Approach 2:
The conversion process is divided into distinct modules: a video analyzing module that processes 2D video content, a depth information generating module that creates depth maps, and a 3D content generating module that synthesizes the final 3D output. This segmentation allows the conversion to be performed efficiently on portable devices.
2Reliability
If 2D video contents are converted to 3D video contents by graphic content providers, then the quality of 3D content is improved, but the device complexity and resource requirements increase
Solution Approach 1:
The portable terminal device performs multiple functions: it acts as a video player, a 3D converter, and a depth map generator. By integrating these functions into a single device, the system eliminates the need for separate conversion equipment, reducing overall system complexity while maintaining 3D content quality.
Solution Approach 2:
The portable terminal autonomously performs the entire 3D conversion process without requiring external conversion equipment or services. The device analyzes 2D video, generates depth information, and creates 3D content independently, simplifying the system architecture.
3Adaptability or versatility
If existing 2D video contents are converted to 3D, then the selection of available 3D content is expanded, but additional resources and modifications to existing content are required
Solution Approach 1:
Users can convert any existing 2D video content to 3D using their portable terminal, eliminating the need for content providers to pre-convert videos. This self-service approach allows immediate access to a vast library of existing 2D content in 3D format without requiring additional content creation resources.
Solution Approach 2:
The conversion process changes the depth parameter of existing 2D video content by generating depth information and creating depth maps. This parameter transformation allows standard 2D videos to be converted to 3D without modifying the original video data, preserving the existing content while adding depth dimensionality.
Data Source
AI summary
A method and device for converting 3D images are disclosed herein. The method include the steps of analyzing a 2-dimensional (2D) image and generating 2D image information, generating a global depth and a local depth by using the generated 2D image information, the global depth corresponding to 3D effect pattern information of the 2D image and the local depth corresponding to 3D effect information of an object included in the 2D image, and generating a depth map by using the global depth and the local depth, wherein the depth map corresponds to 3D effect information of the 2D image, and generating a 3D image configured of a left-eye image and a right-eye image by using the 2D image and the depth map.