Elderly people feature series fusion gesture recognition method and device

A gesture recognition, gesture technology, applied in the field of gesture recognition

Pending Publication Date: 2020-12-18
JIANGSU HUIMING SCI & TECH
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Another example is a gesture recognition system designed and researched based on Kinect. This system uses the length of the finger, the direction

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
  • Elderly people feature series fusion gesture recognition method and device
  • Elderly people feature series fusion gesture recognition method and device
  • Elderly people feature series fusion gesture recognition method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0076] Such as figure 1 As shown, a feature series fusion gesture recognition method for the elderly is characterized in that it comprises the following steps:

[0077] Step S1, gesture image segmentation: using the color space model to convert the RGB image into a YCbCr image, and then using the ellipse model in the skin color model to segment the image to obtain the gesture part;

[0078] Step S2, gesture feature extraction: use the serial feature fusion method to serially fuse the HOG and LBP features, describe the gesture features from the two angles of edge and texture, and adopt the gesture classification and recognition based on SVM;

[0079] Step S3, Valid Gesture Recognition: Use face verification method and head pose estimation method to judge whether the recognized gesture is valid, if valid, use the gesture to identify user needs, otherwise judge it as invalid.

[0080] Specifically, step S1 includes step S11, using a monocular camera to collect images and perform...

Embodiment 2

[0137] The difference between this embodiment and Embodiment 1 is that the head pose estimation method in this embodiment is based on EPnP head pose estimation.

[0138] The EPnP algorithm is to express the three-dimensional coordinates of all feature points in the world coordinate system with the weighted sum of four virtual control point coordinates, and these four virtual control points cannot be coplanar, by solving the coordinates of the four control points in the camera coordinate system Coordinates, the conversion relationship between the coordinates can be obtained, and the posture information of the head can be further calculated according to the conversion relationship.

[0139] Record the coordinates of n feature points in the world coordinate system as The coordinates of the 4 virtual control points are The coordinates projected into the camera coordinate system become The virtual control point becomes Each feature point in the two coordinate systems is re...

Embodiment 3

[0155] An eye movement machine vision tracking device for the elderly, characterized in that it includes a gesture image segmentation module, a gesture recognition module and an effective gesture recognition module;

[0156] The gesture image segmentation module includes a video capture device, a face detection module and a gesture image segmentation submodule; the video capture device collects an image; the face detection module detects a human face in the image collected by the video capture device; the The gesture image segmentation sub-module segments the hand region in the image collected by the video capture device;

[0157] The gesture recognition module includes a gesture feature extraction module and a gesture recognition submodule; the gesture feature extraction module extracts gestures; the gesture recognition submodule compares and recognizes gestures according to preset gesture classifications and extracted gestures;

[0158] The valid gesture recognition module r...

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 relates to an elderly people feature series fusion gesture recognition method and device. The elderly people feature series fusion gesture recognition method comprises the following steps: converting an RGB image into a YCbCr image through a color space model, and segmenting the image through an oval model in a skin color model to obtain a gesture part; performing series fusion on HOG and LBP features by using a series feature fusion method, describing gesture features from two perspectives of edges and textures, and performing SVM-based gesture classification recognition; and determining whether the recognized gesture is valid or not by a face verification method and a head posture estimation method, if so, recognizing a user demand by utilizing the gesture, and otherwise, determining that the gesture is invalid. The current demand of the elderly people is determined through the hand actions of the elderly people, the nursing demand is converted into different hand actions, the problem that the elderly people cannot clearly express the nursing demand in language is indirectly solved, and meanwhile, a simple and easy expression mode is provided for the elderly.

Description

technical field [0001] The invention relates to the technical field of gesture recognition, in particular to a gesture recognition method and device for series fusion of features of the elderly. Background technique [0002] Due to their age, the elderly will degrade their body functions. These elderly people often cannot express their life care needs clearly and intuitively in language due to slurred speech, such as toileting, eating, and medication. [0003] Gesture is an important way for people to communicate information, and people can express rich semantic information through hand movements. Gesture recognition is the process of tracking and recognizing the performed gestures and converting them into words or sentences that can express semantic information. It is mainly divided into two types: static gesture recognition and dynamic gesture recognition. In the research of gesture recognition at home and abroad, many early works relied on various hardware devices to com...

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): G06K9/00G06K9/46G06K9/62
CPCG06V40/113G06V40/28G06V40/161G06V40/168G06V10/56G06F18/2411G06F18/253
Inventor 罗晓君杨金水罗湘喜孙瑜
Owner JIANGSU HUIMING SCI & TECH
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap