18055431. GENERATIVE ADVERSARIAL NETWORK BASED IDENTIFICATION OF INDUCED DEFORMATION IN THREE-DIMENSIONAL OBJECT simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)
Contents
- 1 GENERATIVE ADVERSARIAL NETWORK BASED IDENTIFICATION OF INDUCED DEFORMATION IN THREE-DIMENSIONAL OBJECT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 GENERATIVE ADVERSARIAL NETWORK BASED IDENTIFICATION OF INDUCED DEFORMATION IN THREE-DIMENSIONAL OBJECT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
GENERATIVE ADVERSARIAL NETWORK BASED IDENTIFICATION OF INDUCED DEFORMATION IN THREE-DIMENSIONAL OBJECT
Organization Name
INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s)
Tushar Agrawal of West Fargo ND (US)
Martin G. Keen of Cary NC (US)
Sarbajit K. Rakshit of Kolkata (IN)
Jeremy R. Fox of Georgetown TX (US)
GENERATIVE ADVERSARIAL NETWORK BASED IDENTIFICATION OF INDUCED DEFORMATION IN THREE-DIMENSIONAL OBJECT - A simplified explanation of the abstract
This abstract first appeared for US patent application 18055431 titled 'GENERATIVE ADVERSARIAL NETWORK BASED IDENTIFICATION OF INDUCED DEFORMATION IN THREE-DIMENSIONAL OBJECT
Simplified Explanation
The abstract describes a method, computer system, and computer program product for identifying induced deformation of a 3D object. The process involves receiving a 3D rendering of an object, identifying influencing factors of forecasted local deformation, creating a rendering showing the forecasted deformation, identifying induced deformation in other portions, and creating a rendering showing the induced deformation.
- Identifying induced deformation of a 3D object:
- Receiving an unaltered 3D rendering of an object - Identifying influencing factors of forecasted local deformation based on attribute information - Creating a 3D rendering showing the forecasted local deformation - Identifying induced deformation in other portions caused by the forecasted deformation - Creating a 3D rendering showing the induced deformation
Potential Applications
This technology could be applied in industries such as manufacturing, architecture, and animation to predict and visualize deformations in 3D objects.
Problems Solved
This technology helps in identifying and visualizing induced deformations in 3D objects, which can be crucial for quality control, design optimization, and simulation purposes.
Benefits
The benefits of this technology include improved accuracy in predicting deformations, enhanced visualization of complex deformations, and better understanding of the factors influencing deformations in 3D objects.
Potential Commercial Applications
One potential commercial application of this technology could be in the field of virtual prototyping, where companies can use it to simulate and analyze deformations in their products before physical production.
Possible Prior Art
One possible prior art could be existing 3D modeling and simulation software that offer deformation analysis tools, although the specific method described in this patent application using generative adversarial networks may be a novel approach.
Unanswered Questions
== How does the accuracy of the forecasted local deformation compare to traditional methods? The article does not provide a direct comparison between the accuracy of the forecasted local deformation using this method and traditional methods. Further research or testing may be needed to determine the level of accuracy achieved.
== Are there any limitations to the size or complexity of the 3D objects that can be analyzed using this method? The article does not mention any limitations regarding the size or complexity of the 3D objects that can be analyzed using this method. It would be important to understand if there are any restrictions in terms of object size or complexity for accurate deformation analysis.
Original Abstract Submitted
According to one embodiment, a method, computer system, and computer program product for identifying induced deformation of a 3D object is provided. The embodiment may include receiving an unaltered three-dimensional (3D) rendering of an object and attribute information of the object. The embodiment may include identifying one or more influencing factors of forecasted local deformation of one or more portions of the 3D rendering based on the attribute information. The embodiment may include creating, via a generative adversarial network (GAN), a 3D rendering of the object showing the forecasted local deformation. The embodiment may include identifying induced deformation of one or more other portions of the 3D rendering caused by the forecasted local deformation. The embodiment may include creating, via the GAN, a 3D rendering of the object showing the identified induced deformation.
