Document search for document retrieval using 3D model
AssigneeGeorgetown University
InventorsCristopher Flagg, Ophir Frieder
Life of this patent
Estimating the term…
Abstract
Technologies are described for reconstructing physical objects which are preserved or represented in pictorial records. The reconstructed models can be three-dimensional (3D) point clouds and can be compared to existing physical models and/or other reconstructed models based on physical geometry. The 3D point cloud models can be encoded into one or more latent space feature vector representations which can allow both local and global geometric properties of the object to be described. The one or more feature vector representations of the object can be used individually or in combination with other descriptors for retrieval and classification tasks. Neural networks can be used in the encoding of the one or more feature vector representations.
Claims20
A method, performed by one or more computing devices, the method comprising:
- generating a three-dimensional (3D) model for an object based on one or more epipolar views of the object;
- generating one or more feature vector representations of the 3D model;
- identifying one or more documents having one or more feature vector representations that most closely match the one or more feature vector representations generated for the 3D model;
- wherein the generating the 3D model comprises:
- selecting a point on a first view of the one or more epipolar views;
- projecting a vector from the selected point into a model space;
- projecting the vector onto at least one view of the one or more epipolar views which is not the first view;
- and
- determining one or more candidate points on the vector for the 3D model.
A non-transitory computer-readable medium storing instructions for executing a method via one or more processors, the method comprising:
- generating a three-dimensional (3D) model for an object based on one or more epipolar views of the object;
- generating one or more feature vector representations of the 3D model;
- identifying one or more documents having one or more feature vector representations that most closely match the one or more feature vector representations generated for the 3D model;
- wherein the generating the 3D model comprises:
- selecting a point on a first view of the one or more epipolar views;
- projecting a vector from the selected point into a model space;
- projecting the vector onto at least one view of the one or more epipolar views which is not the first view;
- and
- determining one or more candidate points on the vector for the 3D model.
Dependencies are inferred from the claim text.