Sky Light Probe Estimation Using 3D Model Fitting
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Solution Overview
Problem
Current methods for capturing illumination conditions in image-based lighting technology are expensive, computationally demanding, and inaccessible to casual users, and cannot be applied to images without pre-recorded illumination conditions.
Innovation Solution
A system and method for estimating sky light probes using a camera, processors, and computer-readable media that fit a 3D model to an object in an outdoor image and apply an inverse optimization lighting algorithm to estimate sky light probes, constraining the lighting to a space of precaptured sky light probes, using sun and sky models like the double exponential sun model and Preetham sky model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image-based lighting techniques are used to capture illumination conditions, then accurate lighting information can be obtained, but the equipment cost and computational demand increase significantly
Solution Approach 1:
The patent uses a 3D model copy of the object of interest and applies inverse optimization lighting algorithms to estimate the sky light probe, rather than requiring expensive specialized capture equipment. This copying approach allows accurate illumination estimation using standard camera hardware.
Solution Approach 2:
The patent replaces complex mechanical capture systems (specialized DSLR cameras, chrome spheres) with computational methods (inverse optimization lighting algorithms applied to 3D models), substituting physical measurement complexity with algorithmic processing.
2Measurement precision
If multiple images and calibration objects are used to capture illumination conditions, then accurate sky light probes can be obtained, but the ease of operation decreases
Solution Approach 1:
The system automatically performs 3D model fitting and inverse optimization lighting calculations without requiring user intervention for calibration object placement or multiple coordinated shots. The algorithm self-adjusts to estimate illumination from standard captured images.
Solution Approach 2:
Instead of capturing illumination directly through specialized equipment and calibration objects, the patent inverts the approach by using a 3D model and working backwards through inverse optimization to deduce the illumination conditions from standard images.
3Manufacturing precision
If direct capture of illumination conditions is performed, then photo-realistic relighting can be achieved, but the adaptability to images without pre-recorded illumination decreases
Solution Approach 1:
The patent creates a universal solution that works with any outdoor image regardless of whether specialized illumination capture was performed. The inverse optimization algorithm can process standard images from any device, making the system universally applicable across different image sources and capture conditions.
Data Source
AI summary
Methods and systems for estimating HDR sky light probes for outdoor images are disclosed. A precaptured sky light probe database is leveraged. The database includes a plurality of HDR sky light probes captured under a plurality of different illumination conditions. A HDR sky light probe is estimated from an outdoor image by fitting a three dimensional model to an object of interest in the image and solving an inverse optimization lighting problem for the 3D model where the space of possible HDR sky light probes is constrained by the HDR sky light probes of the database.