Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Gesture classification method based on transfer learning

A technology of transfer learning and classification methods, which is applied in the direction of instruments, calculations, character and pattern recognition, etc., can solve the problems of multiple uses, achieve high classification accuracy, reduce working hours, and improve operating efficiency

Active Publication Date: 2019-10-29
HUAIYIN INSTITUTE OF TECHNOLOGY
View PDF11 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But it should be noted that this algorithm is a binary tree, that is, each non-leaf node can only lead to two branches, so when a non-leaf node is a multi-level (more than 2) discrete variable, the variable has may be used multiple times

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Gesture classification method based on transfer learning
  • Gesture classification method based on transfer learning
  • Gesture classification method based on transfer learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0054] like Figure 1-Figure 4 As shown, a kind of gesture classification method based on transfer learning according to the present invention comprises the following steps:

[0055] Step 1: Convert gesture video V into gesture frame data set G0, specifically as figure 2 Shown:

[0056] Step 1.1: Define V as a gesture video data set, Video as a single video information set, V={Video 1 ,Video 2 ,...,Video a ,...,Video A},Video a is the a-th video information data in V, A is the number of Vi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a gesture classification method based on transfer learning. The gesture classification method is suitable for gesture image classification. The method comprises the steps of 1,converting a gesture video V into a gesture frame data set G0; 2, performing noise removal, binarization and background segmentation processing on the G0 through a Gaussian filtering method, an OTSUalgorithm and image AND operation to obtain a gesture frame data set G1, and setting a label for the G1 to obtain a frame label data set L; 3, carrying out transfer learning by using a MobileNet convolutional neural network architecture and the weight file, and creating and training a model M1; 4, extracting features of the frame data set G1 through the model M1 to obtain a frame feature vector set F0; and 5, classifying the test set by taking the XGBoost as a classification model to obtain a final classification result. According to the method, the weight of the trained MobileNet convolutional neural network is migrated to a gesture image data set for feature extraction, and XGBoost is adopted as a classification model, so that the model calculation amount is reduced while the classification accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of supervisory algorithms and image recognition, in particular to a gesture classification method based on transfer learning. Background technique [0002] When facing the problem of gesture classification, some recent literatures only use a single model to autonomously learn features and classify images, for example: Zhang Jiangxin, Wu Xiaofeng, Xu Xinchen. A gesture detection and recognition method based on Faster R-CNN. China Patent publication number: CN107239731A, 2017.10.10; Cheng Shuying, Lin Peijie, Lu Xiaoyang. A static sign language recognition system based on XGBoost. Chinese patent publication number: CN109086699A, 2018.12.25; Wang Wei, Zou Ting, Wang Xin. A Image classification method based on D-MobileNet neural network. Chinese patent publication number: CN 109214406A, 2019.01.15. This type of method takes a lot of time to train. Some literature proposes an improved method of extracting featu...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/113G06V40/28G06F18/241
Inventor 金鹰王飞胡荣林朱全银董甜甜姚玉婷邵鹤帅施嘉婷
Owner HUAIYIN INSTITUTE OF TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products