Spatiotemporal Alignment for 3D Model Manipulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for interactive spatiotemporal collaboration, such as those using immersive extended reality, face challenges in aligning manipulations across multiple users distributed in time and space due to communication latencies, variance in latency, limited bandwidth, communication errors, reliance on centralized or decentralized networks, and high power and maintenance costs.
Innovation Solution
A method and system for aligning manipulations in time and space by generating a third model based on the first and second models in a global coordinate system, transmitting timing metadata, and updating models with manipulation information, allowing for real-time or near-real-time alignment while minimizing bandwidth and power requirements through localized storage and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized cloud is used to store and distribute model information, then data availability and alignment across devices are improved, but power consumption, security requirements, maintenance costs, and operational expenses increase significantly
Solution Approach 1:
The system segments the centralized cloud storage function into distributed peer-to-peer nodes. Each terminal device maintains local model information and shares it with connected devices, eliminating the need for a centralized cloud infrastructure while maintaining data availability across the network.
Solution Approach 2:
Terminal devices autonomously manage and share model information with each other without requiring centralized cloud services. Each device acts as both a consumer and provider of data, performing self-service operations for storage, retrieval, and synchronization of 3D model information.
2Measurement precision
If all model information (coordinates, orientations, positions) is transmitted between devices, then complete alignment accuracy is achieved, but bandwidth requirements and transmission time increase leading to higher latencies
Solution Approach 1:
The system extracts and transmits only the essential manipulation data (transformation parameters, operation types, timestamps) rather than complete model information. This selective data extraction maintains alignment accuracy while dramatically reducing transmission bandwidth requirements and latency.
Solution Approach 2:
Instead of transmitting all model data, the system transmits partial information sufficient for alignment purposes. The manipulation data includes only the necessary parameters to reconstruct model states at different devices, avoiding redundant data transmission while achieving complete alignment.
3Adaptability or versatility
If decentralized peer-to-peer communication is used to align information across devices, then system autonomy and reduced central dependency are achieved, but security vulnerabilities and error propagation increase
Solution Approach 1:
The system implements feedback mechanisms where terminal devices verify received manipulation data against their local model states. Devices can detect and correct communication errors by comparing expected versus actual model states, and request retransmission of corrupted data, thereby maintaining reliability in decentralized communication.
Solution Approach 2:
The system prepares for potential communication failures by implementing error detection codes, data validation protocols, and fallback mechanisms before errors occur. Manipulation data is packaged with verification information, and devices are prepared to handle missing or corrupted data through predefined recovery procedures.
4Loss of information
If high bandwidth is allocated for transmitting all model information, then complete data synchronization is achieved, but network resource consumption and transmission costs increase
Solution Approach 1:
The system extracts only the minimal necessary data elements for synchronization - manipulation operations, transformation parameters, and timestamps - rather than transmitting complete model datasets. This extraction approach achieves full synchronization of model states while consuming minimal network bandwidth.
Solution Approach 2:
The data transmission is segmented into discrete manipulation events rather than continuous model streams. Each manipulation operation is transmitted as an independent, compact data packet, allowing efficient bandwidth utilization and selective reception based on device needs and network conditions.
Data Source
Figure 1A
Figure 1B
Figure 2~3
AI summary
Disclosed is a method for aligning manipulations in time and space to first model of three-dimensional (3D) real-world object (602) in second model of 3D real-world environment (604) said method comprises: generating, by first terminal device (202, 302, 606), third model based on first model and second model, from first point of view; transmitting third model and timing metadata to second terminal device(s) (204, 304); receiving third model and timing metadata at second terminal device(s); manipulating third model by second terminal device(s); creating manipulation information; transmitting manipulation information from second terminal device(s) to first terminal device; receiving manipulation information at first terminal device; updating, by first terminal device, first model and second model from second point of view; and aligning, by first terminal device, manipulation information in time and space.