Collaborative Workstation Content Alignment and Merging
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Solution Overview
Problem
Existing systems fail to effectively align and merge collaborative content from multiple workstations into a cohesive, scalable, and accurately projected computer-generated output, especially when using off-the-shelf cameras and projectors with varying orientations and unknown positions, leading to distortion and misalignment of virtual and physical content.
Innovation Solution
A method and system that utilize calibrated camera and projector transformations to generate device-independent and scaled images, allowing for the alignment and projection of collaborative content across workstations, using a calibration engine to create transformations based on physical and projector templates, and an alignment engine to ensure proper scaling and orientation on a shared workspace.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If off-the-shelf cameras and projectors with varying orientations and unknown positions are used, then device complexity and cost are reduced, but alignment precision and content accuracy deteriorate
Solution Approach 1:
The system performs preliminary calibration by capturing images of a calibration pattern and computing transformation matrices (camera-to-world and world-to-projector) before actual content projection. This pre-computed transformation data enables accurate alignment without requiring complex real-time adjustment mechanisms, thus maintaining simplicity while achieving precision.
Solution Approach 2:
The patent introduces a calibration pattern as an intermediary object that mediates between the camera and projector. The calibration pattern provides known geometric references that enable the computation of transformation matrices, serving as a bridge that translates between device coordinates and world coordinates without requiring direct complex coordination between camera and projector.
2Adaptability or versatility
If multiple workstations with different camera and projector configurations are used, then system versatility and adaptability improve, but content alignment and merging accuracy deteriorate
Solution Approach 1:
The system employs a universal calibration approach where the same calibration pattern and transformation computation methodology can be applied to any workstation configuration. The transformation matrices serve as a universal translation mechanism that adapts content from any source workstation to any target workstation, regardless of their specific camera and projector configurations.
Solution Approach 2:
The system changes parameters by computing specific transformation matrices for each workstation pair based on their unique configurations. Rather than requiring identical hardware setups, the system adapts to different parameters (camera positions, projector orientations) by calculating appropriate transformation matrices that compensate for these variations, enabling accurate content merging across diverse configurations.
3Measurement precision
If calibrated camera and projector transformations are computed and applied, then content alignment and scaling accuracy improve, but processing time and computational complexity worsen
Solution Approach 1:
The calibration and transformation matrix computation is performed as a preliminary action before actual content sharing occurs. This one-time setup process establishes the transformation relationships that can then be applied efficiently to multiple pieces of content without repeating the complex calculations, thus minimizing processing time for subsequent operations.
Solution Approach 2:
The system captures and stores transformation matrices as computed models of the camera and projector geometries. These stored transformation matrices can be reused and applied to multiple different content images without re-computation, effectively copying the transformation logic across numerous content processing operations to reduce repeated processing time.
Data Source
AI summary
A method for aligning and merging contents from multiple collaborative workstations. Collaborative workstations are multiple workstations that contribute respective contents to be combined into a single computer-generated output. The content generated from each collaborative workstation is the collaborative content. Individual collaborative content is created from each workstation by a user drawing on a piece of paper that is placed on a workspace surface of the workstation. Collaborative contents contributed by multiple workstations are aligned such that a combined product (i.e., a single computer-generated output) including both virtual and physical content appears to be collaboratively drawn by multiple users on a single piece of paper.