Surface Normal Estimation via Bilateral Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image processing systems face challenges in efficiently separating intrinsic color and shading components from input images, especially in dynamic scenes, due to high computational requirements and limited processing resources, which restricts real-time relighting capabilities.
Innovation Solution
An image processing system that determines surface normals by receiving input and depth images, using bilateral filtering to refine coarse estimates based on luminance values, enabling real-time rendering under arbitrary lighting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing is performed offline to separate intrinsic color and shading components, then processing accuracy is improved, but processing time and computational resources increase significantly
Solution Approach 1:
The patent applies preliminary action by performing depth-based surface normal estimation before the actual intrinsic image decomposition process. By pre-computing surface normals from depth images and using them to guide the decomposition, the system reduces the computational complexity of the main processing step, enabling faster online processing while maintaining accuracy
Solution Approach 2:
The patent replaces the traditional iterative optimization-based intrinsic image decomposition with a direct computation method that uses surface normals derived from depth images. This substitution of the computational mechanism eliminates the need for time-consuming iterative solving while preserving decomposition accuracy
2Adaptability or versatility
If conventional intrinsic image processing is applied to video sequences, then dynamic scene relighting capability is improved, but processing complexity and resource requirements increase
Solution Approach 1:
The patent extracts the depth information from video sequences and uses it to compute surface normals independently. This extracted depth-based normal information is then used to simplify the intrinsic image decomposition process for each frame, enabling dynamic scene processing without the full complexity of traditional methods
Solution Approach 2:
The patent changes the computational parameters by using depth-derived surface normals as fixed inputs for the intrinsic image decomposition. This parameter change transforms the problem from solving for surface normals and intrinsic properties simultaneously to only solving for intrinsic properties, reducing complexity for video processing
3Device complexity
If high-quality surface normal estimation is performed without depth images, then algorithm simplicity is improved, but measurement precision of surface normals deteriorates
Solution Approach 1:
The patent merges depth image data with color image processing pipelines. By combining the depth information (which provides accurate geometric constraints) with the color image data, the system achieves high-precision surface normal estimation that leverages both geometric and photometric information
Data Source
AI summary
An image processing system and method for determining a set of surface normals of one or more objects for use in rendering the object(s) is described. One or more input images are received, each representing a view of the object(s). A depth image is received representing depth values of the object(s). Coarse surface normal estimates are determined based on depth values of the received depth image. The set of surface normals are determined by applying bilateral filtering to the coarse surface normal estimates. The bilateral filtering uses bilateral filtering guidance terms based on luminance values derived from the input image, wherein the determined set of surface normals are for use in rendering the object(s).