Polarized Image Normal Line Vector Object Recognition
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Solution Overview
Problem
Existing image analysis technologies face instability in accurately acquiring the position or posture of a target object from a captured image due to factors like appearance, position, and image capturing environment, especially when the target object has few feature points or is small and far from the camera, leading to increased processing load and decreased accuracy.
Innovation Solution
An information processing apparatus that captures polarized images to acquire normal line vectors of a target object's surface, collates these vectors with pre-registered shapes to specify the object's state, and generates output data based on this specification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature points are used to extract a figure of a target object from a captured image, then the processing can be performed using conventional methods, but the accuracy of processing deteriorates if the target object has an insufficient number of feature points or is small and far from the camera
Solution Approach 1:
The patent changes the parameter used for object extraction from feature points to normal line vectors. By utilizing the polarization information to calculate normal line vectors of the target object surface, the system achieves accurate extraction even when the object has few feature points or is small and distant, as normal line vectors provide consistent geometric information independent of object complexity
Solution Approach 2:
The patent introduces normal line vectors as an intermediary element between the captured image and the target object recognition. These vectors serve as a bridge that translates polarization image data into reliable geometric information, enabling accurate object extraction without directly relying on feature points
2Reliability
If the granularity of processing is decreased spatially or temporally to increase robustness in processing accuracy, then the accuracy becomes more stable, but the processing load increases
Solution Approach 1:
The patent replaces complex spatial or temporal processing mechanisms with a more efficient approach based on polarization information analysis. By calculating normal line vectors from polarization angles, the system achieves robust accuracy without requiring fine-grained spatial or temporal processing, thereby reducing computational complexity
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
This approach enables efficient and accurate acquisition of a target object's state from a captured image, reducing errors and processing load by stabilizing normal line vector acquisition and improving matching accuracy.
Implementation Method 1
acquire a distribution of normal line vectors of a target object surface from polarization image information obtained by an imaging apparatus
Data Source
AI summary
A captured image acquisition section 50 acquires, from an imaging apparatus 12, data of a polarized image obtained by capturing a target object and stores the data into an image data storage section 52. A region extraction section 60 of a target object recognition section 54 extracts a region in which a figure of the target object is included in the polarized image. A normal line distribution acquisition section 62 acquires a distribution of normal line vectors on a target object surface in regard to the extracted region. A model adjustment section 66 adjusts a three-dimensional model of the target object stored in a model data storage section 64 in a virtual three-dimensional space such that the three-dimensional model conforms to the distribution of the normal line vectors acquired from the polarized image to specify a state of the target object.