Distributed Projection Calibration via Edge Nodes
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Solution Overview
Problem
Current projector calibration methods are costly and time-consuming, require high-resolution image acquisition using industrial cameras, and are limited by venue and cable installation, leading to potential image transmission interruptions and glitches.
Innovation Solution
A projection calibration method utilizing a distributed system with edge nodes, such as mobile devices, to perform image processing and transmit low-resolution calibration data, reducing the computational load on the center node and minimizing data transmission issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution industrial cameras are used to acquire images for projector calibration, then image quality is improved, but cost and device complexity increase
Solution Approach 1:
The patent replaces expensive industrial cameras with mobile devices (smartphones, tablets) that have built-in cameras. These mobile devices are widely available, cost-effective, and sufficient for calibration purposes when combined with edge computing capabilities to process images locally before transmission.
Solution Approach 2:
The patent uses the built-in camera of mobile devices as a substitute for dedicated industrial cameras. The camera function is copied from specialized equipment to general-purpose devices, eliminating the need for separate expensive imaging hardware while achieving sufficient calibration quality through local image processing.
2Measurement precision
If high resolution images are transmitted to main processor for image processing, then processing accuracy is improved, but data transmission time and computational load increase
Solution Approach 1:
The patent extracts the image processing function from the central processor and relocates it to the edge node (mobile device). The edge node performs image processing locally to extract calibration parameters, then transmits only the processed data rather than raw high-resolution images, significantly reducing transmission time and computational load on the main processor.
Solution Approach 2:
The patent divides the calibration system into edge nodes (mobile devices) and center nodes (main processors). Image processing tasks are segmented and executed at the edge, with only essential calibration parameters transmitted to the center for final calibration operations, creating a distributed processing architecture that optimizes both accuracy and efficiency.
3Area of stationary object
If cameras are installed at high or far positions for calibration, then calibration coverage is improved, but cable length increases and transmission stability deteriorates
Solution Approach 1:
The patent replaces the mechanical cable-based transmission system with wireless communication for transmitting calibration data from mobile devices to the main processor. This eliminates physical cable constraints, allowing cameras to be positioned anywhere within wireless range without worrying about cable length or installation complexity, thereby maintaining transmission stability while improving calibration coverage.
Data Source
AI summary
A projection calibration method includes transmitting a calibration command to an edge node by a center node, acquiring a projection image of a test pattern image by the edge node, performing image processing on the acquired projection n image by the edge node based on the calibration command to get a calibration parameter data, transmitting the calibration parameter data to the center node by the edge node, and outputting a calibration result to a projector by the center node based on the calibration parameter data.