Inverse Rotation Transform for Post-Rotation Panoramic Rendering
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Solution Overview
Problem
Existing panoramic imaging systems face challenges in efficiently generating post-rotation images due to camera rotation, leading to image distortion and the need for frequent triangle division near poles, which complicates the rasterization process.
Innovation Solution
A transform method that involves performing inverse rotation operations on vertices, calculating pre-rotation coordinates, and selecting appropriate texture images to form complete data structures for rendering post-rotation panoramic images, reducing the complexity of image processing and maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the image capture module is rotated to capture different views, then the versatility and adaptability of the panoramic imaging system is improved, but image distortion occurs and triangle division near poles becomes frequent, worsening the device complexity and processing difficulty
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing transformation matrices for various rotation angles before actual rendering. When the camera rotates, the system directly retrieves pre-computed matrices rather than performing complex real-time calculations, thereby maintaining adaptability while reducing processing complexity and avoiding frequent triangle divisions near poles
Solution Approach 2:
The patent changes parameters by transforming vertex coordinates from post-rotation space to pre-rotation space using inverse rotation matrices. This parameter transformation allows the rendering system to work with standardized pre-rotation coordinates regardless of camera orientation, thereby maintaining image quality and reducing the need for complex triangle division operations
2Productivity
If real-time vertex list modification is performed after camera rotation, then the productivity and real-time rendering capability is improved, but the manufacturing precision and image quality may deteriorate due to frequent triangle division
Solution Approach 1:
The patent pre-computes transformation matrices for various rotation angles and stores them in advance. During real-time rendering, the system simply retrieves these pre-computed matrices and applies them to vertex coordinates, achieving both high productivity through fast retrieval and high manufacturing precision by avoiding repeated complex geometric operations that could degrade image quality
3Ease of operation
If the texture coordinates are fixed for each vertex in the modified vertex list, then the ease of operation is improved, but image distortion occurs at poles, worsening the manufacturing precision
Solution Approach 1:
The patent transforms vertex coordinates from post-rotation space to pre-rotation space using inverse rotation matrices before applying texture coordinates. This parameter transformation ensures that texture mapping is always performed in the standardized pre-rotation coordinate system, maintaining manufacturing precision at pole regions while keeping the operation simple through automated coordinate transformation
Data Source
AI summary
A transform method applied in an image processing system is disclosed, comprising: when the image capture module is rotated, respectively performing inverse rotation operations over post-rotation space coordinates of three first vertices from a integral vertex stream according to rotation angles of the image capture module to obtain their pre-rotation space coordinates; calculating pre-rotation longitudes and latitudes of the three first vertices according to their pre-rotation space coordinates; selecting one from a pre-rotation panoramic image, a south polar image and a north polar image as a texture image to determine a texture ID for the three first vertices according to their pre-rotation latitudes; and, calculating pre-rotation texture coordinates according to the texture ID and the pre-rotation longitudes and latitudes to form a first complete data structure for each of the three first vertices.