Automatic Projection Correction Using RGB-D Camera
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Solution Overview
Problem
Current projector systems face challenges in correcting keystone distortion when projecting images non-perpendicularly, especially on complex surfaces like raised blackboards or walls with obstacles, as they rely solely on RGB data, which is insufficient for accurate corner detection and shape correction.
Innovation Solution
An automatic projection correction system utilizing a RGB-D camera that combines RGB and depth information to determine the plane distribution and shape of the projection area, applying a homograph matrix for warp-perspective correction to ensure accurate and distortion-free image projection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If RGB data only is used for corner detection and projection correction, then the system complexity is low, but the measurement precision of projection area shape and position is insufficient
Solution Approach 1:
The patent combines RGB camera and depth camera into an integrated camera system that simultaneously captures both color information and depth information. This merging allows the system to achieve high measurement precision for projection area detection without requiring separate complex detection systems, as both types of data are collected by the integrated camera unit.
Solution Approach 2:
The depth information acts as an intermediary that bridges the gap between simple RGB detection and precise geometric measurement. By introducing depth data as a mediator, the system can accurately determine projection area shape and position without directly complicating the primary RGB-based projection system.
2Reliability
If RGB data only is used for projection correction, then the device complexity is low, but the reliability of correction on complex surfaces is insufficient
Solution Approach 1:
The integration of RGB and depth cameras creates a unified detection system that reliably handles complex surfaces. The depth information provides additional reliability by capturing surface geometry that RGB data alone cannot detect, ensuring accurate projection correction even on raised blackboards or walls with obstacles.
Solution Approach 2:
The system uses composite information from both RGB and depth sensors to create a comprehensive view of the projection surface. This composite data approach enhances reliability on complex surfaces by combining the visual information from RGB with the geometric information from depth sensing, creating a more robust correction system.
3Measurement precision
If depth information is added to RGB data for accurate corner detection, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent merges RGB camera and depth camera into a single integrated system that captures both types of data simultaneously. This merging approach improves corner detection accuracy by combining color and depth information, while avoiding the complexity of separate detection systems by using a unified camera unit.
4Reliability
If depth camera is used to detect projection area shape, then the reliability of projection correction is improved, but the device complexity increases
Solution Approach 1:
The system merges RGB and depth cameras into an integrated unit that simultaneously performs both visual and geometric detection. This merging improves projection correction reliability on complex surfaces by providing depth information, while managing device complexity through a unified camera system design.
Data Source
AI summary
This disclosure describes systems, methods, and devices related to automatic projection correction. A device may generate a first image having a first resolution. The device may project the first image onto a surface resulting in a first projected image on a first projection area. The device may receive input data from a depth camera device, wherein the input data is associated with the first projected image on the first projected area. The device may perform automatic projection correction based on the input data. The device may generate a second image to be projected based on the automatic projection correction. The device may project the second image onto a second projection area.