Multi-Projector Boundary Alignment Using Camera Bounding Boxes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional projection systems using multiple projectors face challenges in aligning projection boundaries due to different camera perspectives, leading to complex and time-consuming image stitching processes and discontinuous boundary lines.
Innovation Solution
A method and system that independently adjust projection boundaries by using a processor to align bounding boxes in captured images from multiple imaging apparatuses, allowing for precise alignment and calculation of a full image boundary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple cameras are used to capture images for defining projection boundary, then the complete projection area can be covered, but the image stitching process becomes complex and time-consuming
Solution Approach 1:
The patent introduces a processor as an intermediary that automatically performs image stitching and boundary calculation. The processor receives images from multiple cameras, automatically stitches them together, calculates the projection boundary based on the stitched image, and generates coordinate data for the projectors. This intermediary device eliminates the need for manual stitching operations while ensuring accurate boundary definition across the complete projection area.
2Measurement precision
If manual image stitching is performed on the application interface to define boundary, then the final overall image can be viewed, but the processing time increases significantly
Solution Approach 1:
The system performs image stitching and boundary calculation in advance through automated processing before the user needs to define the projection boundary. The processor automatically stitches images from multiple cameras, calculates the projection boundary, and generates coordinate data beforehand. This preliminary automated action eliminates the need for time-consuming manual stitching operations when the user needs to adjust the boundary.
3Productivity
If pre-boundary is used for automatic stitching, then the projection boundary can be preset, but the boundaries may not be aligned due to different camera perspectives
Solution Approach 1:
The system uses captured images from multiple cameras as feedback to automatically adjust and align projection boundaries. The processor analyzes the captured images, determines the actual projection boundary based on the captured content and camera perspectives, and generates coordinated boundary data that ensures alignment. This feedback mechanism allows the system to adapt to different camera perspectives and achieve accurate boundary alignment automatically.
Data Source
AI summary
A method for adjusting a projection boundary and a projection system are provided. Multiple imaging apparatuses corresponding to multiple projection apparatuses are driven, and each imaging apparatus obtains a corresponding captured image by capturing projected image projected by corresponding one projection apparatus and surrounding area of the projected image. All captured images are displayed on a display, and a main bounding box corresponding to each projected image and a reference bounding box corresponding to the surrounding area are displayed on each captured image. The main bounding box of each captured image is independently adjusted relative to the reference bounding box to obtain an adjusted main bounding box. A full image boundary is calculated based on the respective adjusted main bounding boxes. The projection apparatuses are driven to project an adjusted full image based on the full image boundary.