Reflective Surface Identification via Back-Ray Tracing
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Solution Overview
Problem
Computer vision systems face challenges in distinguishing between real objects and their reflections, particularly in specular reflections, which can lead to mistaken identification of mirrored surfaces as real objects.
Innovation Solution
A system and method that utilize a sensing device to capture and process images, storing three-dimensional positions of objects and surfaces, and employing a computer processor to identify candidate reflective surfaces by analyzing depth patterns and applying back ray-tracing to differentiate between real and reflective surfaces, generating a spatial representation of reflective surfaces and virtual images accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computer vision systems analyze captured images to identify objects, then object detection capability is improved, but reflective surfaces are mistakenly identified as real objects leading to detection errors
Solution Approach 1:
The patent applies back-ray tracing to invert the usual analysis direction. Instead of tracing light forward from objects to the camera, the system traces rays backward from the camera through the image plane to potential reflective surfaces, then continues tracing to actual objects. This inverted approach allows the system to distinguish between real objects and their reflections by analyzing the geometric consistency of light paths.
Solution Approach 2:
The patent introduces an intermediary computational process between image capture and object identification. The back-ray tracing algorithm acts as a mediator that analyzes potential light paths, identifies reflective surfaces, and resolves ambiguities before final object detection. This intermediary step prevents direct misidentification by inserting a verification layer that checks geometric consistency.
2Measurement precision
If the system attempts to distinguish real objects from reflections, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the scene into distinct components: real objects, reflective surfaces, and virtual images. By dividing the analysis into separate processing streams - one for identifying candidate reflective surfaces and another for tracing light paths - the system manages complexity through modular organization. Each segment handles a specific aspect of the problem, making the overall complex task more tractable.
Solution Approach 2:
The system performs preliminary identification of candidate reflective surfaces before conducting full back-ray tracing. This preliminary action filters out non-reflective surfaces early in the process, reducing the number of surfaces that require computationally intensive ray tracing. By pre-processing and categorizing surfaces, the system reduces overall computational burden while maintaining detection accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate detection and differentiation of reflective surfaces, preventing misidentification and allowing for improved spatial understanding and application in path planning and augmented reality.
Implementation Method 1
The term 'reflective surface' as used herein is defined to be surface that changes the direction of a wavefront (e.g., of light or sound) at an interface between two different media so that the wavefront returns into the medium from which it originated.
Implementation Method 2
Such behavior is described by the law of reflection, which states that the direction of incoming light (the incident ray), and the direction of outgoing light reflected (the reflected ray) make the same angle with respect to the surface normal, thus the angle of incidence equals the angle of reflection and that the incident, normal, and reflected directions are coplanar.
Data Source
AI summary
Methods and a system for identifying reflective surfaces in a scene are provided herein. The system may include a sensing device configured to capture a scene. The system may further include a storage device configured to store three-dimensional positions of at least some of the objects in the scene. The system may further include a computer processor configured to attempt to obtain a reflective surface representation for one or more candidate surfaces selected from the surfaces in the scene. In a case that the attempted obtaining is successful, computer processor is further configured to determine that the candidate reflective surface is indeed a reflective surface defined by the obtained surface representation. According to some embodiments of the present invention, in a case the attempted calculation is unsuccessful, determining that the recognized portion of the object is an object that is independent of the stored objects.