Portable 3D Scanning System with Distributed Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 3D scanning systems face challenges in providing real-time feedback and efficient data processing, especially in portable and handheld devices, which limits user interaction and the quality of 3D models generated, particularly in terms of geometric detail and surface texture fidelity.
Innovation Solution
A 3D scanning system that distributes the computational pipeline between a client-side device and an offline processing system, allowing for real-time image capture, depth map computation, and preview display on the client device, while the offline system processes high-quality 3D mesh models, with configuration settings for model quality, processing, battery life, and server processing, enabling dynamic adjustment based on device conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If all computational processing is performed on the client-side device, then real-time feedback and user interaction are improved, but device complexity and battery consumption increase
Solution Approach 1:
The patent divides the computational pipeline into two segments: real-time processing (depth map computation, preliminary 3D model generation) performed on the client-side device, and high-quality processing (detailed 3D mesh generation, texture mapping) performed on the server-side system. This segmentation allows real-time feedback without overwhelming the client device.
Solution Approach 2:
The patent introduces an intermediary communication layer between client and server that transmits intermediate processing results (depth maps, point clouds) and final results. This intermediary mechanism enables the client to display real-time previews while the server handles intensive computations.
2Manufacturing precision
If high-quality 3D models with detailed geometry and texture are generated, then manufacturing precision is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary processing on the client side to generate depth maps and preliminary 3D models quickly. This preliminary action provides immediate feedback to users, while the high-quality detailed processing is performed subsequently on the server without blocking real-time interaction.
Solution Approach 2:
The patent implements a two-tier processing approach where partial processing (sufficient for real-time feedback) is performed on the client, and excessive/high-quality processing (for maximum detail) is performed on the server. Users can choose to view results at different quality levels based on their needs.
3Device complexity
If computational tasks are distributed to an offline processing system, then device complexity is reduced, but loss of information and processing delays occur
Solution Approach 1:
The patent extracts only the essential intermediate data (depth maps, point cloud coordinates, camera poses) that needs to be transmitted to the server, leaving the heavy computational tasks on the server side. This extraction minimizes data transmission requirements while maintaining processing quality.
Solution Approach 2:
The patent dynamically adjusts processing parameters (model quality settings, resolution levels, detail thresholds) based on device capabilities, network conditions, and user preferences. This allows optimization of the balance between data transmission requirements and processing quality.
4Speed
If real-time depth map computation is performed on the client device, then speed is improved, but use of energy increases
Solution Approach 1:
The patent segments computational tasks by processing type rather than by device, placing real-time depth map computation on the client (energy-intensive but necessary for speed) and high-quality mesh generation on the server (energy-efficient centralized processing). This segmentation optimizes the energy-speed tradeoff.
Solution Approach 2:
The patent implements dynamic parameter adjustment where processing quality levels, resolution settings, and computational intensity are adapted based on battery charge levels, thermal conditions, and network availability. This allows the system to maintain real-time performance when energy is abundant and reduce processing intensity when energy is constrained.
Data Source
AI summary
A method for generating a three-dimensional model of an object, by a scanning system including a client-side device including: an acquisition system configured to capture images; and an interaction system including a display device and a network interface includes: capturing a plurality of images of the object by the acquisition system, the images being captured from a plurality of different poses of the acquisition system; computing depth maps from the images of the objects, each of the depth maps corresponding to one of the poses of the acquisition system; combining the depth maps to generate a combined point cloud; and displaying, on the display device, the combined point cloud or a 3D mesh model generated from the combined point cloud.