Invention Application
- Patent Title: THREE-DIMENSIONAL SHAPE CLASSIFICATION AND RETRIEVAL USING CONVOLUTIONAL NEURAL NETWORKS AND MAJORITY VOTE
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Application No.: US16975411Application Date: 2018-04-20
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Publication No.: US20210104071A1Publication Date: 2021-04-08
- Inventor: Ruiting Shao , Yang Lei , Jian Fan , Jerry Liu
- Applicant: Hewlett-Packard Development Company, L.P.
- Applicant Address: US TX Spring
- Assignee: Hewlett-Packard Development Company, L.P.
- Current Assignee: Hewlett-Packard Development Company, L.P.
- Current Assignee Address: US TX Spring
- International Application: PCT/US2018/028658 WO 20180420
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06K9/62 ; G06T17/00 ; G06N3/04 ; G06N3/08

Abstract:
A deep learning method employs a neural network having three sub-nets to classify and retrieve the most similar 3D model of an object, given a rough 3D model or scanned images. The most similar 3D model is present in a database and can be retrieved to use directly or as a reference to redesign the 3D model. The three sub-nets of the neural network include one dealing with object images and the other two dealing with voxel representations. Majority vote is used instead of view pooling to classify the object. A feature map and a list of top N most similar well-designed 3D models are also provided.
Public/Granted literature
- US11367222B2 Three-dimensional shape classification and retrieval using convolutional neural networks and majority vote Public/Granted day:2022-06-21
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