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Indoor abnormal behavior detection method based on multi-sensor information fusion

A multi-sensor and detection method technology, applied in the direction of sensors, instruments, diagnostic recording/measurement, etc., can solve the problems of poor anti-interference and poor real-time performance

Inactive Publication Date: 2018-01-30
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0003] In order to overcome the shortcomings of poor anti-interference and poor real-time performance of the existing indoor abnormal behavior detection methods, the present invention proposes an anti-interference , Indoor abnormal behavior detection method based on multi-sensor information fusion with good real-time performance

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  • Indoor abnormal behavior detection method based on multi-sensor information fusion
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  • Indoor abnormal behavior detection method based on multi-sensor information fusion

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] refer to Figure 1 ~ Figure 3 , an indoor abnormal behavior detection method based on multi-sensor information fusion, comprising the following steps:

[0039] 1) Data collection

[0040] The data acquisition module is responsible for collecting raw data of human behavior by using various sensors, including acceleration sensors and image sensors;

[0041] Acceleration and other data are collected by wearable terminals worn on the chest and ankles of the human body, and sent to the processor through wireless transmission. The image sensor is deployed in a suitable position to collect human behavior data in a spatial range, and transmits it to the processor through wired transmission.

[0042] For the image data, since the present invention only needs to recognize the posture of the human body in the static image, it only needs a common low-cost USB camera to c...

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Abstract

An indoor abnormal behavior detection method based on multi-sensor information fusion includes the following steps of: 1) data acquisition; 2) sensor data preprocessing: (2.1) original data de-noising, (2.2) sliding window setting, (2.3) amplitude calculation, and (2.4) solution of an attitude angle; and 3) abnormal behavior detection based on acceleration: (3.1) a fall detection algorithm based on double thresholds, (3.2) a motion detection algorithm based on multiple features; and (3.3) an attitude detection algorithm based on the attitude angle. The indoor abnormal behavior detection methodbased on multi-sensor information fusion has good anti-interference performance and good real-time performance.

Description

technical field [0001] The invention belongs to abnormal behavior detection technology, in particular to an indoor abnormal behavior detection method. Background technique [0002] In the traditional abnormal behavior detection research, the collection of human behavior signals mostly uses wearable sensors or image sensors. Behavior detection based on wearable sensors uses portable sensor terminals worn on specific parts of the human body to collect human movement information, and then uses related technologies to realize the behavior recognition of the target human body. The data is intuitive, but it is easily affected by factors such as motion range and sensor performance. Behavior detection based on visual images uses camera equipment to collect images or image sequences in the scene, and then uses image or video processing related technologies to achieve target human body detection and behavior recognition. It does not need to be worn, but is easily affected by factors s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00G06K9/34G06K9/46A61B5/11
Inventor 管秋王捷张寒龙海霞黄志军李康杰王振华
Owner ZHEJIANG UNIV OF TECH
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