Virtual Object Location Correction Using Image-Based Alignment
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Solution Overview
Problem
Current methods for 3D location correction in computer graphic simulations of manufacturing workcells require expensive and complex equipment, multiple steps, and specialized training, making them inefficient and costly for accurate layout and orientation calibration of virtual objects in real-world scenes.
Innovation Solution
A computer-implemented method using a handheld tablet computer with a digital camera and 3D graphical simulation software to capture digital images of real-world scenes and adjust virtual models, allowing for automatic alignment and positional correction of virtual objects based on image-based calculations, eliminating the need for hardware-specific customization and reducing setup time and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive and complex measuring equipment such as coordinate measurement machines, theodolites, and laser range finders are used, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses digital images as copies of the real-world scene containing both physical objects and reference objects. Instead of using complex physical measurement equipment, the system captures optical copies (images) and performs virtual measurements and calculations on these images to determine the real-world locations and orientations of objects, thereby achieving precise location correction without complex measuring devices
Solution Approach 2:
The patent replaces mechanical measurement systems (coordinate measurement machines, theodolites, laser range finders) with a computational approach using digital images and mathematical calculations. The system substitutes physical measurement mechanisms with image processing and geometric calculations to achieve the same location correction function
2Measurement precision
If separate expensive measuring devices are purchased and users are trained to use them, then measurement capability is improved, but ease of operation deteriorates due to training requirements
Solution Approach 1:
The system uses standard digital cameras (including those in mobile devices) that are already widely owned and understood by users. The location correction process automatically performs calculations using the captured images without requiring specialized measurement equipment or extensive training, making the system accessible to general users
Solution Approach 2:
The patent uses universal digital cameras that serve multiple purposes (photography, video, and measurement) rather than specialized measurement devices. The same camera used for ordinary photography can capture images for location correction, eliminating the need for separate dedicated measuring equipment
3Measurement precision
If multiple steps at different locations are required for measurement, then measurement precision is improved, but productivity decreases due to time-consuming processes
Solution Approach 1:
The patent merges the measurement of multiple objects into a single computational process. By capturing all reference objects and virtual objects in one or a few digital images and performing unified mathematical calculations, the system determines the locations and orientations of multiple objects simultaneously, eliminating the need for sequential multi-step measurements at different locations
Data Source
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AI summary
A computer-implemented method is provided for use in location correction of virtual objects in a virtual model of a real-world scene. Location of an object consists of both position and orientation of the virtual object. The method includes generating the virtual model, including a virtual object, and acquiring at least one digital image of a real-world object within the real-world scene, wherein the real-world object corresponds to the virtual object. The method also includes calculating an image-based positional difference between at least one predefined point on the virtual object and at least one corresponding point on the real-world object, adjusting the position and/or the orientation of the virtual object based on this image positional difference, and adjusting the virtual model with respect to the corrected location of the virtual object.