View source for 18279685. ESSENTIAL MATRIX GENERATION APPARATUS, CONTROL METHOD, AND COMPUTER-READABLE MEDIUM simplified abstract (NEC Corporation)

=ESSENTIAL MATRIX GENERATION APPARATUS, CONTROL METHOD, AND COMPUTER-READABLE MEDIUM=


==Organization Name==

[[:Category:NEC Corporation|NEC Corporation]]


[[Category:NEC Corporation]]

==Inventor(s)==

[[:Category:Gaku Nakano of Tokyo (JP)|Gaku Nakano of Tokyo (JP)]][[Category:Gaku Nakano of Tokyo (JP)]]

==ESSENTIAL MATRIX GENERATION APPARATUS, CONTROL METHOD, AND COMPUTER-READABLE MEDIUM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18279685 titled 'ESSENTIAL MATRIX GENERATION APPARATUS, CONTROL METHOD, AND COMPUTER-READABLE MEDIUM

==Simplified Explanation==

The patent application describes an apparatus for generating an essential matrix, which represents an epipolar constraint between points on two images. The apparatus detects feature point pairs from two images, then derives point pairs based on these feature points to generate the essential matrix.

* Detecting three or more feature point pairs from a first image and a second image
* Detecting derived point pairs for each feature point pair, based on distances in different directions
* Generating an essential matrix representing the epipolar constraint using the detected feature point pairs and derived point pairs

== Potential Applications ==
This technology could be applied in:
* Computer vision systems
* Robotics for navigation and object recognition
* Augmented reality applications

== Problems Solved ==
This technology helps solve:
* Matching points between images for 3D reconstruction
* Improving accuracy of camera calibration
* Enhancing object tracking in real-time applications

== Benefits ==
The benefits of this technology include:
* Increased accuracy in determining the relationship between points in images
* Improved performance in computer vision tasks
* Enhanced capabilities for 3D reconstruction and object recognition

== Potential Commercial Applications ==
A potential commercial application for this technology could be in:
* Developing advanced surveillance systems
* Creating autonomous vehicles with improved perception capabilities
* Enhancing medical imaging technologies

== Possible Prior Art ==
One possible prior art for this technology could be:
* Previous methods for calculating essential matrices in computer vision applications

=== Unanswered Questions ===

=== How does this technology compare to existing methods for generating essential matrices in terms of accuracy and efficiency? ===
This technology offers improved accuracy and efficiency compared to existing methods by incorporating derived point pairs in the essential matrix generation process.

=== What are the computational requirements for implementing this apparatus in real-time applications? ===
The computational requirements for real-time implementation of this apparatus depend on the complexity of the images and the number of feature point pairs detected. Further research is needed to determine the exact computational resources needed for different scenarios.


==Original Abstract Submitted==

An essential matrix generation apparatus performs: detecting three or more feature point pairs from a first image and a second image; detecting, for each of two or more of the feature point pairs, a derived point pair that is a pair of a derived point separated by a first distance in a first direction from a point on the first image included in the feature point pair and a derived point separated by a second distance in a second direction from a point on the second image included in the feature point pair; generating an essential matrix representing an epipolar constraint on a point on the first image and a point on the second image by using the detected feature point pairs and derived point pairs.



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