Manual alphabet identification method based on RGB-D image

A RGB-D and recognition method technology, applied in the field of computer vision behavior recognition, can solve problems such as negative effects, low recognition accuracy, and easy misjudgment of intra-class difference samples

Inactive Publication Date: 2015-01-07
NANJING UNIV OF POSTS & TELECOMM
View PDF3 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Some researchers have proposed some methods for sign language recognition using RGB-D data. For example, a Chinese invention patent application discloses a "Gesture recognition method based on a small number of training samples composed of RGB-D data" (application date is 2013 -10-29, the publication date is 2014-01-22, and the application number is 201310522370.7), this method can use less RGB-D data samples to realize gesture recognition, but the patent uses complex optical flow tracking algorithm to detect human motion points of interest, the computational complexity is high; in addition, the random distribution of non-zero coefficients in the sparse feature vector generated by the traditional sparse coding method used in this patent reduces the inter-class separation characteristics of sparse features; finally, the patent uses the recent The final result is judg

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
  • Manual alphabet identification method based on RGB-D image
  • Manual alphabet identification method based on RGB-D image
  • Manual alphabet identification method based on RGB-D image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0045] The idea of ​​the present invention is to have different hand texture information according to different sign language letter types, and extract HOG (Histogram of Oriented Gradient, histogram of gradient direction) features and SNV (Super Normal Vector (Supernormal Vector) features, using the combination of PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) to optimize the feature attributes to obtain significant feature attributes, and further use the group dictionary (BoW) to sparse The representation method sparsely represents the features; using contrast mining technology (Contrast Mining) to obtain representative template instances (Exemplars) in each sign language letter category. Finally, a hierarchical judgment strategy based on greedy thinking is adopted. First, the non-parametric kNN (k-Nearest Neighbor Algorithm)...

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 manual alphabet identification method based on an RGB-D image, and belongs to the technical field of behavior identification of computer vision. According to different types of hand texture information of different types of manual alphabets, histogram-of -oriented-gradient characteristics and super-normal-vector characteristics of an RGB-D image video frame obtained through an RGB-D camera are extracted; a principal component analysis and a linear discrimination analysis are combined for characteristic attribute optimizing processing, so that a characteristic attribute with saliency is obtained, and BoW sparse representation is conducted on the characteristics; a data contrast mining technology is used for obtaining representative exemplars in all the types of manual alphabet; finally, a hierarchy judgment policy based on a greedy thought is adopted, the manual alphabets easy to classify are quickly classified through a nonparametric k-Nearest Neighbor Algorithm classifier firstly, and the manual alphabets difficult to classify are judged through a trained support vector machine model based on templates. Compared with the prior art, the manual alphabet identification method is high in both identification accuracy and identification efficiency.

Description

technical field [0001] The invention relates to a sign language letter recognition method, in particular to a sign language letter recognition method based on an RGB-D image, and belongs to the technical field of computer vision behavior recognition. Background technique [0002] Deaf-mute people account for a large part of human society, but it is difficult for deaf-mute people to integrate into social life. This is because the deaf-mute use sign language as the main way of communication, but the reality is that most ordinary people cannot understand sign language, which hinders the integration of the deaf-mute into society. The purpose of studying sign language recognition is to establish a communication bridge between the deaf-mute and ordinary people, and realize barrier-free information exchange between the deaf-mute and ordinary people. Sign language is a human language that integrates a variety of human communication methods including gestures, expressions, and lip m...

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): G06K9/00G06K9/36G06K9/62
CPCG06V40/28G06V10/20G06F18/2411
Inventor 裴启程袁建敏陈克虎丁菲刘天亮霍智勇
Owner NANJING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products