Patent · US Active

Deep learning based method and apparatus for three dimensional model triangular facet feature learning and classifying

US10049299B2 · kind B2 · utility

0Cited by

1References

10Claims

0Family size

Assignee

Beihang University · CN

Inventors

Xiaowu Chen · Miaocheng, CN
Kan Guo · Beijing, CN
Dongqing Zou · Beijing, CN
Qinping Zhao · Beijing, CN

Key dates

Filing date	Feb 22, 2017
Grant date	Aug 14, 2018
Priority date	—
Expiry date	Mar 23, 2037

Classification

Technology area (CPC G)Physics
CPC primaryG06V20/64
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

The invention discloses a deep learning based method for three dimensional (3D) model triangular facet feature learning and classifying and an apparatus. The method includes: constructing a deep convolutional neural network (CNN) feature learning model; training the deep CNN feature learning model; extracting a feature from, and constructing a feature vector for, a 3D model triangular facet having no class label, and reconstructing a feature in the constructed feature vector using a bag-of-words algorithm; determining an output feature corresponding to the 3D model triangular facet having no class label according to the trained deep CNN feature learning model and an initial feature corresponding to the 3D model triangular facet having no class label; and performing classification. The method enhances the capability to describe 3D model triangular facets, thereby ensuring the accuracy of 3D model triangular facet feature learning and classifying results.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.