3D Scene Model Rendering Using Compressed Image Features
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Solution Overview
Problem
Existing neural radiance field techniques for rendering two-dimensional images from different view angles suffer from low quality and inefficiency due to reliance solely on camera pose and view angle information for determining color and depth information.
Innovation Solution
A method that involves acquiring a three-dimensional scene model, a target camera pose, and a target view angle, determining a target compressed image feature, and inputting these elements to the three-dimensional scene model for rendering a target image, utilizing the compressed image feature as a reference basis for improved quality and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If neural radiance field techniques rely solely on camera pose and view angle information for rendering, then the rendering process is simple, but the image quality is low and details are unclear
Solution Approach 1:
The patent applies preliminary action by pre-compressing image features from multiple view angles and storing them before rendering. When generating a target image, the system retrieves and utilizes these pre-computed compressed image features along with camera pose and view angle information. This preliminary preparation of image features enables higher image quality and clearer details without adding complexity to the actual rendering process, as the feature compression and storage are performed in advance.
2Productivity
If compressed image features are used as auxiliary conditions for rendering, then image generation efficiency improves, but the processing complexity increases
Solution Approach 1:
The patent applies copying by creating compressed representations (copies) of image features from multiple view angles. Instead of processing original high-dimensional image data during rendering, the system uses these compressed feature copies that capture essential visual information. This copying approach improves image generation efficiency by reducing data processing requirements while the systematic organization of feature compression and retrieval minimizes the added processing complexity.
Data Source
AI summary
Embodiments of the present disclosure provide a method for image generation for a particular view angle. The method comprises acquiring a three-dimensional scene model, a target camera pose, and a target view angle corresponding to a target scene. The method further comprises determining a target compressed image feature corresponding to the target camera pose and the target view angle from a plurality of compressed image features. The method further comprises inputting the target camera pose, the target view angle, and the target compressed image feature to the three-dimensional scene model, and obtaining a target image corresponding to the target camera pose and the target view angle through rendering by the three-dimensional scene model. By using embodiments of the present disclosure, it is possible to acquire a more accurate rendered image from a target view angle while saving the storage memory and increasing the loading speed.