Virtual Sensor Parameter Generation for Deterministic Scene Setup
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Solution Overview
Problem
Generating realistic synthetic scenes with accurate camera and lighting settings is difficult, time-consuming, and costly due to the complexity of virtual cameras and the need for expert knowledge, while current AI models provide non-deterministic results that are input-specific and limit scalability.
Innovation Solution
Utilizing trained large language models (LLMs) and vision language models (VLMs) to generate deterministic camera and lighting settings by parsing user inputs, modifying them to conform to desired formats, and integrating them into content generation environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If expert knowledge is used to establish camera settings, then the quality of scene representation is improved, but the cost and time consumption increase
Solution Approach 1:
The patent creates virtual cameras that copy the functional behavior of physical cameras through software simulation. These virtual cameras replicate real camera parameters (aperture, focal length, shutter speed) and lighting interactions, enabling automated scene generation without requiring physical camera equipment or expert operators. The virtual camera system copies essential camera functions while eliminating the need for expert knowledge in scene setup.
Solution Approach 2:
The system enables self-service by allowing automated generation of camera settings and scene parameters through programmable interfaces. The virtual camera system can automatically adjust parameters based on scene requirements without human intervention, and the programmable nature allows the system to serve itself by generating its own configuration data through algorithms and data structures.
2Extent of automation
If virtual cameras are used to generate scene representations, then automation is improved, but the device complexity increases
Solution Approach 1:
The virtual camera system is segmented into distinct functional components represented by data structures: camera intrinsic parameters (focal length, aperture, sensor dimensions), extrinsic parameters (position, orientation), and operational parameters (shutter speed, ISO). This segmentation allows each component to be independently configured and managed, reducing overall system complexity while maintaining high automation capability.
Solution Approach 2:
The virtual camera implementation provides multi-functionality by simulating various physical camera types and parameters within a single software system. The same virtual camera framework can represent different camera models, lenses, and sensor configurations through parameter adjustment, eliminating the need for multiple specialized devices and simplifying the overall system architecture.
3Manufacturing precision
If detailed camera parameters are specified for high quality representation, then the realism is improved, but the ease of operation deteriorates
Solution Approach 1:
The patent introduces an intermediary layer between the user and the complex camera parameters. This intermediary consists of standardized data structures and programmable interfaces that translate high-level scene requirements into detailed camera settings. The intermediary handles the complexity of parameter specification internally, allowing users to work with simplified concepts while maintaining access to detailed parameters when needed.
Data Source
AI summary
Approaches presented herein provide systems and methods for generating one or more parameters for a content generation environment. One or more trained models may be used to generate parameters for the content generation environment based on a provided input. The input may be evaluated and then parsed or otherwise formatted to generate a deterministic output from the one or more trained models. A modified input generated from the input may then be provided to the one or more models for generation of the requested parameters. A configuration file may be generated and/or the parameters may be directly provided to an environment to configure different components based on the generated parameters.