Local image enhancement-based home appliance gesture quick detection identification method

A partial image and recognition method technology, which is applied in the field of gesture recognition, can solve the problems of gesture misrecognition, missed recognition, and low input quality, so as to avoid false recognition and missed recognition and improve user experience.

Active Publication Date: 2018-05-15
RECONOVA TECH CO LTD
View PDF10 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a method for fast detection and recognition of home appliance gestures based on local image enhancement, which solves the problem of incorrect and missed recognition of gestures caused by the low quality of image input in existing gesture recognition, thereby improving user experience

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
  • Local image enhancement-based home appliance gesture quick detection identification method
  • Local image enhancement-based home appliance gesture quick detection identification method
  • Local image enhancement-based home appliance gesture quick detection identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] Such as Figure 1 to Figure 4 As shown, the present invention discloses a method for fast detection and recognition of home appliance gestures based on partial image enhancement, which includes the following steps:

[0039] Step 1. Offline detection and recognition model training

[0040] The offline refers to a model learned in advance before the specific home appliance gesture recognition runs; the model is a knowledge base learned in advance.

[0041] Step 1.1, Human Hand Raising Posture Model Training

[0042] By collecting pictures and videos of various lighting and distances of people's hand gestures, such as figure 2 As shown, the circumscribed rectangular frame of the upper body and the arm is manually calibrated as the positive sample, and then a large number of pictures of other scenes and poses are selected as the negative sample, and the positive and negative samples are sent to the deep convolutional neural network detector for learning, and it is possib...

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 a local image enhancement-based home appliance gesture quick detection identification method. The method comprises the steps of extracting a motion region in an image sequenceby adopting a mobile detection method; in the motion region, detecting a hand raising posture of a person by adopting a detection algorithm, and locating a hand region; performing local enhancement on the hand region; and identifying specific gestures by utilizing an identification algorithm. According to the home appliance gesture quick detection identification method, the hand region is subjected to image enhancement, so that the region is clearer, remote home appliance gesture control of multiple complex light rays can be adapted, the problems of false identification and missing identification caused by unclear gestures are effectively avoided, and the user experience is improved.

Description

technical field [0001] The invention relates to the field of gesture recognition, in particular to a method for fast detection and recognition of home appliance gestures based on partial image enhancement. Background technique [0002] Gesture control is a very convenient method in home appliance control. Gesture control has the characteristics of non-contact, fast and convenient. [0003] At present, gesture recognition is generally realized based on images, which has the advantages of long recognition distance and low cost. However, this recognition is more dependent on image quality and needs to deal with various complex lighting environments. Simply adjusting the global ISP cannot make the image of some areas of the hand clear, and unclear gestures are likely to cause misrecognition and missed recognition. This leads to false triggering and missing responses of instructions, resulting in poor user experience. Contents of the invention [0004] The purpose of the pres...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V40/28G06N3/045
Inventor 贾宝芝黄春辉梅海峰
Owner RECONOVA TECH CO LTD
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