An abnormal state detection method for a person needing special care

Abstract

The invention relates to an abnormal state detection method for a person needing special care. The method comprises the following characteristics of intelligently maintaining the scene background image, keeping the background scene image in the latest state at any time; identifying the scene areas, boundaries and specific targets in advance; carrying out the human detection and tracking; judging the posture of human body from the detected human body image; synthesizing the aforementioned characteristics, analyzing the different gestures and time parameters of different areas in the monitoringscene, and judging whether to be abnormal or not. The method is based on the computer vision field and adopts a machine learning method to detect the abnormal state of human body, and has the advantages of low equipment cost, timely discovery, high detection accuracy and strong robustness.

Description

technical field [0001] The invention relates to a computer vision-based abnormal state detection method for persons requiring special care. Background technique [0002] With the development of the times, the society pays more and more attention to vulnerable groups such as the elderly, the sick, and the disabled. Many of the more vulnerable people have to live alone for a variety of reasons, such as the elderly living alone at home, the blind, and the sick in wards. With the increase of labor costs, many vulnerable people cannot be effectively cared for and protected. Once they encounter an emergency that causes them to fall, faint, lose consciousness or self-help ability, and cannot be discovered by others in time, it is very likely to endanger their lives. As of 2018, there are about 240 million elderly people and about 85 million disabled people in my country. The care of vulnerable people has become an important issue in today's society. [0003] At present, the equi...

AI Technical Summary

Problems solved by technology

It is impossible to judge the situation where the face is blocked or the face cannot be recognized

[0005] The current gesture recognition method also has the following shortcomings: 1. The gesture is generally judged based on a single frame, and multiple frames are not jointly judged, which is prone to misjudgment

2. The recognition method is relatively simple, lack of maintenance of the background, changes in light and shadow, movement of furniture and objects will interfere with recognition

3. The human body posture, time, position and other parameters are not combined and analyzed, and the current human state cannot be well distinguished

4. There is no targeted training for application scenarios. The training picture set is downloaded from the Internet, which does not match the product camera parameters and actual usage scenarios, and the training classification effect is not good.

Images