View source for 20240045062. AUGMENTED ILLUMINATION AND 3D DIMENSIONING (AI3D) FROM 3D RECONSTRUCTION WITHIN A SINGLE-POSE IMAGE simplified abstract (KIHOMAC, Inc.)

=AUGMENTED ILLUMINATION AND 3D DIMENSIONING (AI3D) FROM 3D RECONSTRUCTION WITHIN A SINGLE-POSE IMAGE=


==Organization Name==

[[:Category:KIHOMAC, Inc.|KIHOMAC, Inc.]]


[[Category:KIHOMAC, Inc.]]

==Inventor(s)==

[[:Category:Brian Stearmer of Vienna VA (US)|Brian Stearmer of Vienna VA (US)]][[Category:Brian Stearmer of Vienna VA (US)]]

==AUGMENTED ILLUMINATION AND 3D DIMENSIONING (AI3D) FROM 3D RECONSTRUCTION WITHIN A SINGLE-POSE IMAGE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240045062 titled 'AUGMENTED ILLUMINATION AND 3D DIMENSIONING (AI3D) FROM 3D RECONSTRUCTION WITHIN A SINGLE-POSE IMAGE

==Simplified Explanation==

The abstract of the patent application describes a system that assesses the military load classification (MLC) of a bridge, aiming to enhance soldier survivability and engineer reconnaissance support in the military decision-making process (MDMP). The system utilizes various 3D dimensioning solutions, including soldier-guided vector-based measurements, photogrammetry, computer vision (CV), and augmented reality (AR) methodologies. These solutions enable off-image plane measurements across all three axes of the image through the image principal point. The system incorporates a single image with a view of the bridge feature, camera focal length, camera sensor width, laser rangefinder (LRF) vector to the image principal point, and two lines traced along the edges of the bridge to identify one vanishing point. By utilizing these techniques, a rapid MLC calculation can be performed from a considerable distance, even greater than 100 meters, as long as there is an unobstructed "below-deck" view of the bridge.

* Soldier-guided, vector-based measurements
* Photogrammetry
* Computer vision (CV)
* Augmented reality (AR) methodologies
* Off-image plane measurements across all three axes
* Single image with a view of the bridge feature
* Camera focal length
* Camera sensor width
* Laser rangefinder (LRF) vector to the image principal point
* Two lines traced along the edges of the bridge to identify one vanishing point
* Rapid MLC calculation from a considerable distance

Potential Applications:
- Military load classification assessment of bridges
- Soldier survivability enhancement
- Engineer reconnaissance support in the military decision-making process (MDMP)

Problems Solved:
- Difficulty in assessing the military load classification (MLC) of bridges
- Limited operator expertise required for MLC assessment
- Inadequate support for military decision-making process (MDMP)

Benefits:
- Increased soldier survivability
- Enhanced engineer reconnaissance support
- Reduction in required operator level of expertise
- Improved military decision-making process (MDMP)


==Original Abstract Submitted==

a bridge military load classification (mlc) assessment system may increase soldier survivability and/or engineer reconnaissance support to military decision-making process (mdmp) while reducing the required operator level of expertise. a set of “at distance” 3d dimensioning solutions may include soldier-guided, vector-based measurements, photogrammetry, and/or computer vision (cv) and augmented reality (ar) methodologies-enabling off image plane measurements along all three axes across the image through the image principal point. the solutions may include (1) single image with view of bridge feature that introduces two- or three-point perspective, (2) camera focal length, (3) camera sensor width, (4) laser rangefinder (lrf) vector to the image principal point, and (5) two lines traced along edges of the bridge to identify one vanishing point. a rapid mlc could be calculated from a considerable distance (greater than 100 meters) given an unobstructed “below-deck” view of the bridge.



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