Lenticular Image Generation Using Offline Mesh Mapping
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Solution Overview
Problem
Conventional methods for generating lenticular images are computationally intensive and power-consuming, as they require rendering images for multiple viewpoints in real-time, leading to misalignment issues when head-mounted devices (HMDs) move during use.
Innovation Solution
A method where a fixed 3D mesh is generated offline, and real-time texture information is mapped to it, using pre-generated UV maps to create lenticular images for multiple viewpoints, reducing real-time computation and power consumption, and incorporating sensors to detect movement and adjust the number of viewpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional methods render images for multiple viewpoints in real-time, then lenticular images can be displayed from different angles, but computational load and power consumption increase significantly
Solution Approach 1:
The patent pre-renders images for multiple viewpoints offline before the HMD is worn, storing them in a frame buffer. During actual use, the system only needs to retrieve and display pre-rendered frames corresponding to detected head orientations, avoiding real-time rendering computations and significantly reducing power consumption while maintaining multi-viewpoint display capability
Solution Approach 2:
The system dynamically adjusts the number of viewpoints rendered based on detected head movement. When the HMD is stationary, fewer viewpoints are needed; when movement is detected, the system renders additional viewpoints to maintain image quality, optimizing the balance between computational load and display quality in real-time
2Adaptability or versatility
If conventional methods render images for multiple viewpoints in real-time, then lenticular images can be displayed from different angles, but computational complexity increases
Solution Approach 1:
The patent pre-renders images for multiple viewpoints offline before the HMD is worn, storing them in a frame buffer. During actual use, the system only needs to retrieve and display pre-rendered frames corresponding to detected head orientations, avoiding real-time rendering computations and significantly reducing computational complexity while maintaining multi-viewpoint display capability
Solution Approach 2:
The rendering process is segmented into offline pre-rendering and online frame selection. The complex multi-viewpoint rendering is performed once offline, while the online phase only requires simple frame buffer access and display, dividing the computational burden into manageable stages that reduce overall system complexity
3Adaptability or versatility
If the HMD moves during use, then the user can view from different angles, but image misalignment occurs with conventional real-time rendering
Solution Approach 1:
The patent pre-renders images for multiple viewpoints offline, creating a comprehensive set of pre-calculated frames that account for various head orientations. When the HMD moves, the system selects from these pre-rendered frames based on detected orientation, ensuring accurate image alignment without real-time computation delays or misalignment issues
Solution Approach 2:
The system uses sensors to detect head orientation and movement in real-time, providing feedback that determines which pre-rendered frames to display. This closed-loop feedback mechanism ensures that the displayed images remain aligned with the user's actual viewing angle, maintaining precision even as the HMD moves
4Adaptability or versatility
If real-time rendering is performed for multiple viewpoints, then dynamic texture information can be displayed, but processing time increases
Solution Approach 1:
The patent pre-renders the base images for multiple viewpoints offline, storing them in a frame buffer. During use, only texture information needs to be applied to these pre-rendered frames, significantly reducing processing time compared to full real-time rendering while still allowing dynamic texture updates to reflect current scene information
Data Source
AI summary
Methods and apparatus for generating images to be displayed on lenticular displays. In these methods, a fixed mesh is generated offline, and in real-time texture information is mapped to the fixed mesh. In an offline process, texture and 3D mesh information for an object is used to render UV map views for multiple viewpoints of the object, view maps are generated from display calibration data, and a lenticular to UV map is generated from the UV map views and view maps. In real-time, texture information is captured, and a composite process is performed that generates a lenticular image for multiple viewpoints by sampling pixels from the texture based on the lenticular to UV map. The lenticular image is then displayed on the lenticular display. Detected positions of persons in the environment may be used to limit the number of viewpoints that are generated during the real-time composite process.