Mixed Reality Lighting Model from Autonomous Shadow Sampling
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Solution Overview
Problem
Existing lighting models are limited in space and fail to provide accurate, dynamic lighting conditions for large mixed reality scenes, especially in real-time renderings, due to variations in light intensity and occlusions, making realistic shadow rendering challenging.
Innovation Solution
An autonomous device equipped with a camera moves through an environment, capturing images from different positions to analyze lighting conditions, generating a lighting model by tracking shadows and estimating light source positions, directions, and intensities, which are then combined into a common coordinate system for accurate lighting representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a lighting model is created for a large scene by capturing lighting from multiple positions, then the spatial coverage and accuracy of lighting representation is improved, but the time required to collect sufficient lighting data increases
Solution Approach 1:
The system performs preliminary lighting data collection by capturing images at multiple predetermined positions along a planned trajectory before actual rendering. This advance data gathering allows the lighting model to be pre-computed and stored, eliminating the need for time-consuming real-time measurements during rendering operations.
Solution Approach 2:
The system uses a moving autonomous device that dynamically changes position to capture lighting conditions from multiple viewpoints. The device follows a predetermined trajectory through the scene, automatically adjusting its position to collect comprehensive lighting data that accurately represents the entire spatial environment.
2Reliability
If shadow rendering is performed with high accuracy by tracking light sources and occluders, then the realism of the rendered scene is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system pre-computes shadow maps by analyzing lighting conditions and occluder positions at multiple captured positions before rendering. These pre-computed shadow relationships are stored and reused during rendering, avoiding the need for complex real-time shadow calculations while maintaining high visual realism.
Solution Approach 2:
The system creates simplified representations of complex lighting and shadow relationships by capturing actual lighting conditions and occluder positions, then using these captured data sets as substitutes for complex physical light transmission calculations. This copying approach maintains realism while reducing computational burden.
3Adaptability or versatility
If lighting conditions are continuously estimated to adapt to dynamic changes, then the realism and accuracy of lighting representation is improved, but the processing time and computational resources increase
Solution Approach 1:
The system adapts to dynamic lighting changes by capturing images at multiple positions along a predetermined trajectory, allowing the lighting model to reflect current environmental conditions. This dynamic data collection approach enables the system to update its lighting representation while maintaining real-time rendering performance through efficient trajectory-based sampling.
Data Source
AI summary
Estimating lighting conditions in a mixed reality scene is a challenging task. Adding shadows cast by virtual objects in the scene contributes significantly to the user experience. To this end, there is proposed, among others, a method for an autonomously movable device having a camera. The device may move to a first position in the scene and capture a first image of a shadow of the device cast by a light source. The device may move to a second position in the scene and capture a second image of a shadow of the device cast by a light source. Features of the light source may be determined at each of the first and the second positions, and a lighting model may be determined for the scene based on the determined features of the light source in the scene.