Automated Synthetic Scene Generation with Physical Plausibility Control
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Solution Overview
Problem
Existing methods for generating synthetic scenes lack control over the realistic insertion of rare objects, often resulting in objects being generated in an unrealistic manner due to the lack of precise control over size, orientation, and position.
Innovation Solution
The method involves providing scene data, object data, and scene parameters to generate intermediate representations where selected objects are inserted into template scenes based on physical plausibility, using generative models like diffusion models conditioned by ControlNet.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single text prompt and mask are used for inpainting, then the generative model has freedom in generating objects, but the desired object is not generated in a sufficiently realistic manner
Solution Approach 1:
The patent applies parameter changes by introducing multiple control parameters beyond simple text prompts and masks. Specifically, it uses shape masks, depth maps, normal maps, and segmentation masks to precisely control the generation parameters of objects. This allows the generative model to maintain freedom while generating realistic objects by constraining key geometric and spatial parameters.
Solution Approach 2:
The patent introduces intermediate representations as mediators between the text prompt and the final generated image. These intermediate representations include depth maps, normal maps, and segmentation masks that serve as bridging structures to guide the generative model in producing realistic objects while maintaining control over their properties.
2Reliability
If object characteristics are manually established for automated insertion, then physical plausibility is ensured, but the process requires complex human intervention
Solution Approach 1:
The patent implements self-service by enabling the system to automatically extract object characteristics from the scene environment without manual intervention. The generative model uses the provided depth maps, normal maps, and segmentation masks to self-determine appropriate object parameters such as size, orientation, and position that ensure physical plausibility within the scene context.
Solution Approach 2:
The patent applies preliminary action by pre-processing the scene data to extract and prepare all necessary parameters (depth maps, normal maps, segmentation masks) before the actual object insertion process. This preliminary preparation of scene understanding data enables automated physical plausibility checking and parameter adjustment without requiring human intervention during the insertion process.
3Manufacturing precision
If generative models are used to generate photorealistic synthetic images, then image quality is improved, but control over object insertion is reduced
Solution Approach 1:
The patent applies segmentation by dividing the control of object insertion into multiple independent components: shape masks for object boundaries, depth maps for spatial positioning, normal maps for orientation control, and segmentation masks for scene understanding. This segmentation of control mechanisms allows precise control over object insertion while maintaining photorealistic image quality generated by the generative model.
Data Source
AI summary
The invention relates to a method (100) for an automated generation of synthetic scenes (175), comprising the following steps:providing (101) scene data (110) representing a plurality of template scenes (120),providing (102) object data (115) specifying various objects (125) for insertion into the synthetic scene (175),providing (103) at least one scene parameter (130) for the template scenes (120), which describes at least one characteristic of the template scenes (120),generating (106) intermediate representations (140) for the synthetic scenes (175), wherein, regarding the intermediate representations (140), at least one selected object (125) is in each case inserted into a selected template scene (120), wherein the insertion of the at least one selected object (125) is parametrized based on the provided scene parameter (130) in order to account for physical plausibility in the respective intermediate representation (140),determining (107) conditioning data (150) from the generated intermediate representations (140) in order to also account for physical plausibility in the synthetic scenes (175),initiating (108) the generation of the synthetic scenes (175) based on the determined conditioning data (150).