Stereoscopic 3D Image Depth Manipulation via Non-Linear Disparity Mapping
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Solution Overview
Problem
Current methods for adjusting the depth of stereoscopic images require professional knowledge and are restrictive, lacking intuitive and simple solutions for users to manipulate depth effectively in post-production processes.
Innovation Solution
A non-linear disparity mapping function is introduced, utilizing a histogram analyzing unit, Gaussian mixture model fitting, disparity adjusting, and recalculating units to allow users to adjust depth layers and optimize disparity maps, enabling intuitive depth manipulation through parameter adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional depth adjustment methods are used, then depth manipulation can be performed, but user operation complexity increases and intuitiveness decreases
Solution Approach 1:
The patent transforms complex depth adjustment operations into simple parameter changes by introducing a non-linear disparity mapping function. Users can adjust depth by modifying parameters (e.g., disparity values, mapping coefficients) rather than navigating complex interfaces, thereby improving ease of operation while reducing operational complexity.
Solution Approach 2:
The patent replaces manual, mechanical depth adjustment processes with automated computational methods. By using algorithms to calculate and optimize disparity mapping functions, the system substitutes complex manual operations with automated parameter optimization, making depth adjustment more intuitive and easier to perform.
2Adaptability or versatility
If professional knowledge is required for depth adjustment, then adjustment precision can be maintained, but user accessibility decreases
Solution Approach 1:
The patent enables the system to perform depth adjustment automatically based on user-selected parameters, eliminating the need for professional knowledge. The automated algorithms handle the complex calculations and optimizations, allowing ordinary users to achieve precise depth manipulation through simple parameter input without requiring expertise in stereoscopic image processing.
Solution Approach 2:
The patent introduces an intermediary layer in the form of automated algorithms and computational models. This intermediary translates simple user parameter inputs into precise depth adjustments, bridging the gap between user accessibility and adjustment precision. The intermediary handles the complex transformations while presenting a simplified interface to the user.
3Adaptability or versatility
If restrictive rendering processes are used, then stereoscopic content requirements can be met, but flexibility for depth manipulation decreases
Solution Approach 1:
The patent introduces dynamic adjustment capabilities through the non-linear disparity mapping function. Instead of fixed, restrictive rendering processes, the system allows real-time, flexible depth manipulation by dynamically adjusting mapping parameters. This enables adaptability while reducing the rigidity and restrictions of conventional rendering pipelines.
Solution Approach 2:
The patent segments the depth adjustment process into independent parameter adjustments. By dividing the complex depth manipulation task into separate controllable parameters (e.g., disparity values, layer positions, mapping coefficients), the system provides flexible control points that can be adjusted independently, increasing versatility while simplifying the overall process structure.
Data Source
AI summary
Provided are an apparatus and a method for manipulating depth of a stereoscopic image that enable a user to manipulate depth of a stereoscopic image easily and intuitively. The apparatus may include: a histogram analyzing unit acquiring a depth distribution chart by performing histogram analysis of a disparity map corresponding to an input image; a Gaussian mixture model (GMM) fitting unit acquiring multiple depth layers by performing GMM fitting of the depth distribution chart; a disparity adjusting unit adjusting at least one of a position and a volume of at least one of the multiple depth layers and calculating a disparity mapping function on which a result of the adjustment is reflected in response to a user request; and a disparity map recalculating unit calculating a new disparity map by optimizing the disparity mapping function.