Audio-Driven Image Synthesis Using Landmark Spatial Structure
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Solution Overview
Problem
Existing image synthesis methods using NeRF technology face challenges in adapting to diverse audio/landmark inputs due to fixed MLP parameters and information loss during audio feature extraction, leading to poor synthesis quality.
Innovation Solution
Perform spatial structure encoding on landmarks without additional feature extraction operations like smoothing or compression, using the landmark's spatial structure as the encoding object to obtain a spatial structure feature, and determine a sampling point based on the image capture device's position and pixel preview to generate a synthetic image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If additional feature extraction operations (smoothing or compression) are performed on landmarks, then the processing complexity is reduced, but information loss occurs leading to decreased synthesis quality
Solution Approach 1:
The patent extracts only the essential spatial structure information from landmarks while discarding unnecessary processing steps. By directly using landmark coordinates to construct spatial structure features without additional smoothing or compression operations, the method removes harmful information loss while maintaining processing efficiency.
Solution Approach 2:
The patent changes the parameter representation from processed features (smoothed/compressed) to raw spatial coordinates. By transforming the landmark data representation method rather than applying complex processing operations, the system achieves both low complexity and high information retention.
2Device complexity
If fixed MLP parameters are used in NeRF technology, then the model structure is simplified, but adaptability to diverse audio/landmark inputs deteriorates
Solution Approach 1:
The patent introduces dynamic adaptability into the previously static MLP parameter structure. By making the spatial structure features dynamically adjustable based on different audio and landmark inputs, the system maintains a relatively simple model structure while achieving high adaptability to diverse inputs.
Solution Approach 2:
The patent changes the parameters fed into the MLP from fixed pre-processed features to dynamically generated spatial structure features. This parameter transformation allows the model to adapt to diverse inputs without increasing structural complexity.
3Ease of operation
If audio feature extraction is performed, then audio processing is enabled, but information loss occurs leading to poor synthesis quality
Solution Approach 1:
The patent introduces spatial structure features as an intermediary between raw audio inputs and the synthesis process. This intermediary representation preserves essential spatial information while enabling effective audio processing, avoiding the information loss associated with direct feature extraction methods.
4Loss of information
If spatial structure encoding is performed without additional feature extraction operations, then information completeness is improved, but processing complexity increases
Solution Approach 1:
The patent extracts precisely the necessary spatial structure information directly from landmark coordinates without performing unnecessary additional processing operations. This selective extraction approach maintains information completeness while avoiding the complexity increase that would result from multiple processing stages.
Solution Approach 2:
Instead of applying multiple processing operations to reduce complexity, the patent inverts the approach by using the raw coordinate data directly. This inversion eliminates unnecessary processing steps while maintaining information completeness, achieving both goals simultaneously.
Data Source
AI summary
In an image synthesis method, one or more landmarks of a target image are determined. The one or more landmarks are processed to obtain a spatial structure feature of each of the one or more landmarks. A sampling point is determined based on a position of an image capture device and a pixel in a preview of the target image provided by the image capture device. A position feature of the sampling point is determined. An audio signal is mapped to the one or more landmarks of the target image. A synthetic image of the target image is generated according to the spatial structure feature of (i) the one or more landmarks, (ii) the audio signal, and (iii) the position feature of the sampling point.