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1. CN109492612 - Fall detection method based on skeleton points and a fall detection device thereof

Office China
Application Number 201811433808.3
Application Date 28.11.2018
Publication Number 109492612
Publication Date 19.03.2019
Publication Kind A
IPC
G06K 9/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/62
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
A61B 5/11
AHUMAN NECESSITIES
61MEDICAL OR VETERINARY SCIENCE; HYGIENE
BDIAGNOSIS; SURGERY; IDENTIFICATION
5Measuring for diagnostic purposes; Identification of persons
103Measuring devices for testing the shape, pattern, size or movement of the body or parts thereof, for diagnostic purposes
11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
CPC
A61B 5/1117
AHUMAN NECESSITIES
61MEDICAL OR VETERINARY SCIENCE; HYGIENE
BDIAGNOSIS; SURGERY; IDENTIFICATION
5Detecting, measuring or recording for diagnostic purposes
103Detecting, measuring or recording devices for testing the shape, pattern, ; colour,; size or movement of the body or parts thereof, for diagnostic purposes
11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
1116Determining posture transitions
1117Fall detection
A61B 5/1128
AHUMAN NECESSITIES
61MEDICAL OR VETERINARY SCIENCE; HYGIENE
BDIAGNOSIS; SURGERY; IDENTIFICATION
5Detecting, measuring or recording for diagnostic purposes
103Detecting, measuring or recording devices for testing the shape, pattern, ; colour,; size or movement of the body or parts thereof, for diagnostic purposes
11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
1126using a particular sensing technique
1128using image analysis
G06K 9/00342
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
00335Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
00342Recognition of whole body movements, e.g. for sport training
G06K 9/6256
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
6256Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
G06K 9/6267
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6267Classification techniques
Applicants PING AN TECHNOLOGY (SHENZHEN) CO., LTD.
平安科技(深圳)有限公司
Inventors ZHOU TAOTAO
周涛涛
ZHOU BAO
周宝
CHEN YUANXU
陈远旭
XIAO JING
肖京
Agents 北京英特普罗知识产权代理有限公司 11015
Title
(EN) Fall detection method based on skeleton points and a fall detection device thereof
(ZH) 基于骨骼点的跌倒检测方法及其跌倒检测装置
Abstract
(EN)
The invention provides a fall detection method and device based on skeleton points, and the method comprises the steps: training a first feature extraction neural network through a first image sample,and enabling the first feature extraction neural network to be used for extracting a plurality of first feature points which represent key skeleton points on a human body; inputting a second video sample into the trained first feature extraction neural network to obtain a plurality of second feature points representing key skeleton points of a human body in the second video sample; encoding the plurality of second feature points to generate a prediction feature map; training a second behavior classification neural network through the prediction feature map, wherein the second behavior classification neural network is used for classifying behaviors represented in the prediction feature map; and sequentially inputting the video data of the monitored object into the trained first feature extraction neural network and the trained second behavior classification neural network so as to output the behavior category of the monitored object.

(ZH)
本发明提供一种基于骨骼点的跌倒检测方法及其装置,所述方法包括:通过第一图片样本训练第一特征提取神经网络,所述第一特征提取神经网络用于提取表征人体上的关键骨骼点的多个第一特征点;将第二视频样本输入训练好的所述第一特征提取神经网络,得到表征所述第二视频样本中的人体的关键骨骼点的多个第二特征点;对所述多个第二特征点进行编码生成预测特征图;通过所述预测特征图训练第二行为分类神经网络,所述第二行为分类神经网络用于对所述预测特征图中表示的行为进行分类;将被监测对象的视频数据依次输入训练好的所述第一特征提取神经网络和所述第二行为分类神经网络,以输出所述被监测对象的行为类别。

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