Light Source Estimation via Iterative Rendering and Error Minimization
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Solution Overview
Problem
Existing methods for estimating light sources in real scenes are inefficient, require significant user effort, and often result in unstable processing due to high computational load and local optimization issues, especially when comparing computer-generated and actual images.
Innovation Solution
A camera-based information processing device that estimates light sources by acquiring image data, shape data, and image capturing conditions, using an initial light source data determination and derivation process to optimize light source data through iterative rendering and error minimization, allowing for efficient and stable light source estimation without the need for specialized apparatus or extensive user movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the method by Japanese Patent Laid-Open No. 2008-33531 is used to estimate light source by acquiring entire periphery image, then light source estimation can be performed, but the user must move in the entire periphery direction which requires significant time and effort
Solution Approach 1:
The patent pre-calculates and stores light source distribution data for various camera positions and orientations before actual image capture. This preliminary preparation allows the system to quickly retrieve and compare pre-rendered images with the captured image, eliminating the need for time-consuming real-time rendering or user movement to acquire multiple images.
Solution Approach 2:
The patent creates computer-generated copy images based on the captured image and compares them to estimate the light source. By generating synthetic images with controlled lighting conditions and comparing them to the actual captured image, the system can determine the most likely light source configuration without requiring physical movement or additional image capture.
2Measurement precision
If the method by Okabe is used to estimate light source by comparing CG image data with actually photographed image data, then light source parameters can be optimized, but the large number of light source parameters causes optimization to take much time and results in local solutions making processing unstable
Solution Approach 1:
The patent extracts only the essential light source parameters needed for accurate estimation, removing unnecessary parameters from the optimization process. By focusing on key parameters such as light source position, intensity, and color temperature while excluding redundant parameters, the system achieves stable and reliable results without falling into local optimization traps.
Solution Approach 2:
The patent transforms the light source parameter representation to a more manageable form that reduces the search space for optimization. By changing how light source parameters are defined and represented, the system can efficiently find the global optimum without being constrained by the large parameter space that causes instability in traditional methods.
3Manufacturing precision
If traditional image processing is performed to change light source kind and direction or synthesize virtual objects, then the intended effect can be achieved, but a skilled person must spend much time to create a processed image without unnaturalness
Solution Approach 1:
The patent enables automatic light source estimation and image processing without requiring skilled manual intervention. The system autonomously analyzes the captured image, estimates light source parameters, generates appropriate processed images, and ensures naturalness through automated comparison with pre-calculated reference data, thereby achieving high quality results rapidly.
Solution Approach 2:
The patent employs feedback mechanisms where the system continuously compares generated processed images with the original captured image and pre-calculated reference images to ensure naturalness. This automated feedback loop allows the system to adjust processing parameters in real-time, achieving high-quality results without manual intervention and significantly improving processing speed.
Data Source
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AI summary
Conventional calculation of light source data requires a high load and is unstable. An information processing device derives light source data which represents a state of a light source of an image represented by a captured image based on image capturing condition data at the time of capturing the image of a subject.