Projector Gestural Control and Auto-Correction
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Solution Overview
Problem
Projection devices face challenges in maintaining image quality due to improper alignment, non-planar surfaces, and objects between the projector and the projection surface, leading to distortion and discomfort, especially when projecting onto dynamic and irregular surfaces.
Innovation Solution
A device with a camera and processor that captures images of the projection surface, calculates corrections for distortions, and applies compensation to the image data to improve projection quality by accounting for keystone, shifts, and surface irregularities, using techniques such as projecting a target grid for auto-correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the projector is positioned at an angle to the projection surface, then the projector can reach difficult-to-access locations, but keystone distortion occurs
Solution Approach 1:
The system performs preliminary capture of the projection surface geometry and objects before displaying the final image. The camera captures the surface and objects, the processor calculates distortion corrections in advance, and then applies these corrections to the image data before projection, ensuring geometric accuracy is pre-established
Solution Approach 2:
The system uses a camera to capture feedback information about the actual projection surface and objects in the projection path. This captured image data is fed back to the processor, which compares it with the source image and uses the difference information to calculate and apply real-time distortion corrections, creating a closed-loop control system
2Productivity
If a person or object is placed between the projector and the projection screen, then the projection can reach the intended surface, but distortion occurs at the obstruction point
Solution Approach 1:
The camera captures the projection surface and objects in real-time, providing feedback about obstructions. The processor compares the captured image with the source image to detect objects between the projector and surface, then calculates compensation data to correct the distortion caused by these obstructions
Solution Approach 2:
The system dynamically changes the projection parameters by applying distortion correction transformations to the image data based on the detected objects and surface geometry. The processor modifies the image coordinates and pixel mapping to compensate for obstructions, effectively changing the projection parameters in response to environmental conditions
3Adaptability or versatility
If the projection surface is non-planar or irregular, then the projector can adapt to various environments, but the projected image becomes distorted
Solution Approach 1:
The system performs preliminary capture of the projection surface geometry before image display. The camera captures the surface characteristics, the processor calculates the distortion pattern in advance by comparing with a reference plane, and pre-computes the correction transformation to be applied to the image data
Solution Approach 2:
The camera provides continuous feedback about the projection surface geometry. The processor uses this feedback to calculate real-time distortion corrections by comparing the captured surface image with the source image, and applies the computed compensation to maintain geometric fidelity on irregular surfaces
4Temperature
If the projector is miniaturized and integrated with other devices, then portability is improved, but the projection output quality and alignment precision deteriorate
Solution Approach 1:
The integrated camera provides feedback about the actual projection surface and alignment conditions. The processor uses this feedback to calculate real-time correction data that compensates for misalignment and surface irregularities, allowing the miniaturized projector to achieve accurate projection despite its compact size and integration with other devices
Solution Approach 2:
The system performs self-alignment and self-correction by using its own camera to capture the projection surface and calculate the necessary corrections. The processor automatically generates compensation data without external intervention, enabling the portable device to self-optimize its projection output quality
Data Source
AI summary
Gestures may be performed to control a visual projector. When a device or human hand is placed into a projection field of the visual projector, the visual projector responds to gestures. The human hand, for example, may gesture to rotate a projected image or to correct the projected image. The visual projector may thus manipulate and/or correct the projected image in response to the gesture.


