Synthetic World Simulation for Computer Vision and Speech Testing
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Solution Overview
Problem
Designing computer vision and speech algorithms is challenging due to the complexity of environment, motion, and sensor configurations, leading to high costs and long development times in manual testing processes.
Innovation Solution
A synthetic world interface is used to model digital environments, sensors, and motions, facilitated by a library of sensor primitives and motion generators, enabling rapid testing of hardware configurations and algorithms in a virtual environment through a sensor platform simulator, motion orchestrator, environment orchestrator, and experiment generator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual testing processes are used for computer vision and speech algorithms, then development can be performed with basic tools, but development time and cost increase significantly
Solution Approach 1:
The patent creates virtual copies of physical sensors, environments, and motion scenarios in a synthetic world interface. These virtual representations allow algorithm testing without requiring physical prototypes and real-world deployment, enabling rapid iteration by copying and modifying virtual configurations rather than building physical test setups.
Solution Approach 2:
The system pre-generates synthetic training data and test scenarios before algorithm development begins. By preparing virtual environments, sensor configurations, and motion patterns in advance, the patent eliminates the need for time-consuming data collection in the field during the development phase, significantly accelerating the testing and optimization process.
2Reliability
If comprehensive hardware configuration testing is performed manually, then algorithm performance can be optimized, but testing cost and complexity increase
Solution Approach 1:
The synthetic world interface serves multiple functions simultaneously: it acts as a sensor platform simulator, motion orchestrator, environment generator, and experiment manager all in one system. This multi-functional virtual platform can test various hardware configurations without requiring separate physical test setups for each scenario, reducing overall system complexity while maintaining comprehensive testing capability.
Solution Approach 2:
The patent introduces a virtual intermediary layer between the algorithm and physical hardware. This synthetic world interface mediates the testing process by providing virtual sensor data and environments, allowing algorithm evaluation without direct connection to complex physical testing infrastructure, thereby simplifying the overall system while maintaining reliability.
3Measurement precision
If extensive synthetic data generation is performed, then algorithm training quality improves, but computational resources and processing time increase
Solution Approach 1:
The system generates synthetic data with varying degrees of complexity and completeness based on specific testing needs. Rather than exhaustively generating all possible scenarios, the patent selectively creates data that is sufficient for the current algorithm version and testing objectives, reducing unnecessary computational expenditure while maintaining adequate training quality.
Solution Approach 2:
The synthetic data generation process is dynamic and adaptive, adjusting the level of detail and complexity based on the algorithm's performance and development stage. The system can increase or decrease data generation intensity as needed, optimizing the balance between training quality and computational resource consumption throughout the development lifecycle.
Data Source
AI summary
A synthetic world interface may be used to model digital environments, sensors, and motions for the evaluation, development, and improvement of computer vision and speech algorithms. A synthetic data cloud service with a library of sensor primitives, motion generators, and environments with procedural and game-like capabilities, facilitates engineering design for a manufactural solution that has computer vision and speech capabilities. In some embodiments, a sensor platform simulator operates with a motion orchestrator, an environment orchestrator, an experiment generator, and an experiment runner to test various candidate hardware configurations and computer vision and speech algorithms in a virtual environment, advantageously speeding development and reducing cost. Thus, examples disclosed herein may relate to virtual reality (VR) or mixed reality (MR) implementations.