Projector Structured-Light Reprojection After Abnormal Capture Detection
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Solution Overview
Problem
Existing projection methods using structured lights are affected by disturbances such as ambient light, leading to incomplete image capturing and inefficient optimization of the number of projected structured lights.
Innovation Solution
A method that involves capturing multiple structured light images, identifying any abnormal captures, and adjusting the number of projected structured lights based on the captured data, including or excluding the abnormal ones, and adjusting for changes in projector position or posture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If M structured lights are projected onto the display surface, then the completeness of image capturing is improved, but the time required for projection and capturing is increased
Solution Approach 1:
The system dynamically adjusts the number of structured lights to be projected based on real-time detection of capture abnormalities. When abnormalities are detected, the system modifies the projection plan from M lights to N lights (where N < M), optimizing the process adaptively rather than using a fixed number of lights.
Solution Approach 2:
The system implements a feedback mechanism where the capture results of structured lights are evaluated, and abnormal captures are identified. This feedback information is then used to adjust subsequent projection operations, determining whether to reproject the same number of lights or reduce the number to N lights based on the detected abnormalities.
2Measurement precision
If all M structured lights are reprojectored when capture abnormalities occur, then the accuracy of image data is maintained, but the overall processing time is increased
Solution Approach 1:
Instead of reprojecting all M structured lights when abnormalities occur, the system applies partial action by selecting only N lights (where N < M) for reprojection. This partial approach maintains sufficient accuracy while improving processing efficiency.
Solution Approach 2:
The system changes the parameter of the number of structured lights from M to N based on the detection results. This parameter adjustment allows the system to optimize between accuracy and speed by adapting the number of lights to the actual capture conditions.
3Productivity
If the number of structured lights is reduced to N when abnormalities are detected, then the processing time is reduced, but the risk of incomplete data increases
Solution Approach 1:
The system dynamically determines whether to use N lights or M lights for reprojection based on the specific abnormality detection results. This dynamic decision-making process balances the trade-off between processing efficiency and data completeness on a case-by-case basis.
Data Source
AI summary
A projection method includes: acquiring a plurality of pieces of captured image data by capturing an image of each of M structured lights projected from a projector onto a projection target with a camera, M being a natural number equal to or greater than 2; determining, based on the plurality of pieces of captured image data, whether at least one first structured light whose image is not normally captured, of the t M structured lights, is present; and projecting N structured lights including the at least one first structured light onto the projection target, N being a natural number smaller than M, when it is determined that the at least one first structured light is present.