Task-aware point cloud down-sampling
AssigneeInterDigital Patent Holdings, Inc.
InventorsHaiyan Wang, Jiahao Pang, Muhammad Asad Lodhi, Dong Tian
Life of this patent
Estimating the term…
Abstract
A method includes generating, using a neural network, a point-level feature vector for each point of a point cloud and a set-level feature vector for the point cloud. A representative position is generated based on the point-level feature vectors and on the set-level feature vector. The representative position and the set-level feature vector is output as a set descriptor.
Claims20
A method comprising, for a point cloud:
- generating, for each point of the point cloud, a point-level feature vector by inputting a position vector of the point in a neural network, and generating a set-level feature vector for the point cloud by using the neural network;
- generating a representative position based on the point-level feature vectors and on the set-level feature vector;
- and
- outputting the representative position and the set-level feature vector as the set descriptor.
(canceled)
A method for retrieving a point cloud from a data stream, the method comprising:
- obtaining, from the data stream, a down-sampled point cloud, a residual point cloud and a set-level feature vector;
- feeding the down-sampled point cloud and the set-level feature vector to a predictor construction module to obtain a predicted point cloud;
- and
- retrieving the point cloud by adding up the predicted point cloud to the residual point cloud.
(canceled)
A device comprising a processor associated with a memory, the processor being configured to, for a point cloud:
- generate, for each point of the point cloud, a point-level feature vector by inputting a position vector of the point in a neural network, and generate a set-level feature vector for the point cloud by using the neural network;
- generate a representative position based on the point-level feature vectors and on the set-level feature vector;
- and
- output the representative position and the set-level feature vector as the set descriptor.
(canceled)
A device for retrieving a point cloud from a data stream, the device comprising a processor associated with a memory, the processor being configured to:
- obtain, from the data stream, a down-sampled point cloud, a residual point cloud and a set-level feature vector;
- feed the down-sampled point cloud and the set-level feature vector to a predictor construction module to obtain a predicted point cloud;
- and
- retrieve the point cloud by adding up the predicted point cloud to the residual point cloud.
(canceled)
Dependencies are inferred from the claim text.