Illuminant Estimation Using Shadow Point Cloud Matching
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Solution Overview
Problem
Existing illuminant estimation techniques struggle to accurately predict the position of illuminants, especially when they are out of the visual range or in scenarios with multiple objects, leading to incorrect shadow directions and low prediction accuracy.
Innovation Solution
An illuminant estimation method and apparatus that acquires two image frames, detects shadows, extracts pixel feature points, determines point cloud information, matches shadows with objects, and calculates the illuminant position using a positional relation between objects and shadows, emitting rays from edge points to highest object points or using an illumination estimation model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-sensor calibration and fusion or regional texture analysis is used to predict illuminant position, then prediction capability is improved, but device complexity and requirements for number and layout of devices increase
Solution Approach 1:
The patent extracts and utilizes only the necessary visual information from images (shadows and objects) to determine illuminant position, rather than requiring multiple sensors or complex device layouts. The method extracts pixel feature points from shadow regions and matches them with object point clouds to calculate illuminant position, simplifying the device requirements while maintaining prediction capability
Solution Approach 2:
The patent creates a virtual 3D point cloud representation of shadows from 2D image data, copying the essential spatial information needed for illuminant position calculation without requiring physical 3D sensors. This virtual modeling approach achieves accurate prediction using standard imaging devices
2Measurement precision
If mirror reflection spheres and ray tracing are used to predict illuminant position, then prediction capability is improved, but requirements for features of reference objects increase
Solution Approach 1:
The patent converts the typically problematic shadow regions into useful information sources for illuminant position determination. Instead of treating shadows as obstacles or noise, the method extracts pixel feature points specifically from shadow regions and uses them to calculate illuminant position, turning a challenge into an advantage
Solution Approach 2:
The patent replaces complex optical mechanisms like mirror reflection spheres and ray tracing with a computational geometry approach using point cloud matching and ray emission from shadow points. This substitution uses standard image processing and mathematical calculations instead of specialized optical hardware
3Illumination intensity
If first illuminant estimation technique calculating overall brightness and color temperature is used, then environmental reflection effect quality is improved, but illuminant direction prediction capability deteriorates
Solution Approach 1:
The patent segments the image into distinct regions (shadows and objects) and processes them separately to extract spatial relationship information. By dividing the visual data into meaningful components and analyzing their geometric relationships, the method simultaneously achieves accurate illuminant position prediction while maintaining environmental reflection quality
Data Source
AI summary
An illuminant estimation method, including acquiring two image frames, wherein a distance between the two image frames is greater than a predetermined distance; detecting shadows included in the two image frames, extracting pixel feature points corresponding to the shadows, determining point cloud information about the shadows, and distinguishing a point cloud of each shadow based on the point cloud information about the shadows; acquiring point cloud information about multiple objects, and distinguishing a point cloud of each object based on the point cloud information corresponding to the multiple objects; matching the point cloud of the each shadow and the point cloud of the each object in order to determine corresponding shadows associated with the multiple objects; and determining a position of an illuminant according to a positional relation between the multiple objects and the corresponding shadows.