Depth Identification of Pixels in 3D Images
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Solution Overview
Problem
Converting 2-D multimedia content to stereoscopic 3-D content is labor-intensive, requiring specialized computer graphics skills and significant manual labor, especially when animating objects, as it involves recreating the entire image in a virtual 3-D environment, which is time-consuming and prone to inaccuracies in depth perception.
Innovation Solution
A method and system that analyze a 2-D image to determine depth pixel offsets, generate a depth map by coloring pixels based on their depth, and apply identifiers to selected pixels, allowing for easier adjustment of perceived depth and simplifying the conversion process by extracting layers and applying pixel offsets to create stereoscopic effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If virtual 3-D environment recreation is used to convert 2-D to stereoscopic 3-D, then depth perception accuracy is improved, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent segments the image processing into distinct layers (foreground, midground, background) and applies different pixel offsets to each layer. This segmentation allows automated processing of depth information while maintaining accurate depth perception, resolving the contradiction between precision and productivity by dividing the complex task into manageable, automatable components.
Solution Approach 2:
The patent performs preliminary analysis to automatically determine depth characteristics of different image regions before applying stereoscopic effects. By pre-identifying objects, layers, and their spatial relationships, the system prepares depth offset parameters in advance, enabling efficient automated conversion while preserving depth accuracy without requiring manual recreation of the entire 3-D environment.
2Productivity
If manual layer extraction and pixel offset application is used, then conversion time is reduced, but depth accuracy and quality deteriorate
Solution Approach 1:
The patent incorporates feedback mechanisms where the system analyzes the extracted layers and adjusts pixel offsets based on detected depth characteristics, object boundaries, and spatial relationships. This automated feedback loop ensures that even with faster processing, the depth accuracy is maintained by continuously optimizing offset parameters based on the actual image content and desired stereoscopic effect.
3Manufacturing precision
If specialized computer graphics skills are required for 2-D to 3-D conversion, then depth quality is improved, but ease of operation decreases
Solution Approach 1:
The patent implements self-service automation where the system automatically performs layer extraction, depth analysis, and pixel offset application without requiring manual intervention or specialized graphics skills. The automated algorithms analyze image content, identify depth cues, and apply appropriate stereoscopic effects, enabling users with basic skills to achieve professional-quality depth conversion while maintaining high depth quality through sophisticated automated processing.
Data Source
AI summary
The present application includes a computer implemented method including at least two modes for analyzing a stereoscopic image corresponding to a two dimensional image. The method includes analyzing one or more layers of the two dimensional image to determine a depth pixel offset for every pixel in the two dimensional image and creating by the processing element a depth map, such as a gray scale map, by coloring every pixel a color shade based on the respective depth pixel offset for the pixel. The method further includes displaying on a display an output image corresponding to the stereoscopic image, receiving a first user selection corresponding a first depth pixel offset, determining a plurality of pixels of the output image corresponding to the first depth pixel offset, and applying a first identifier to the plurality of pixels on the output image corresponding to the first depth pixel offset. Additionally, in a first mode the output image displayed includes the first identifier and in a second mode the output image displayed includes the depth map and the first identifier.