Adaptive threshold multi-target falling detection method based on video processing

Abstract

Provided is an adaptive threshold multi-target falling detection method based on video processing. According to the technical scheme, the method includes following steps: step 1, acquiring image information of users, and recording an aspect ratio, an effective area ratio and a center change of a human body image in a minimum external rectangle of the user during normal activity and falling; step 2, giving different weights to different sensitive degrees of falling by employing the aspect ratio and effective area ratio of the human body image, obtaining new determination parameters, and realizing fusion of falling determination modes; step 3, setting optimal thresholds for users of different body types; and step 4, realizing target falling detection according to the acquired image information of the users in step 1 and the fusion of the falling determination modes in step 2 and with the combination of the set optimal falling thresholds of the users in step 3. According to the method, the defect that people easily forget and contradict wears in a wearable type falling detection scheme is overcome, and difficulties of high misjudgment rate, expensive price and inconvenient laying dueto an environment type falling detection system are solved.

Description

Technical field: [0001] The invention relates to a detection method for people falling, in particular to a video processing-based self-adaptive threshold multi-target detection method for people falling. Background technique: [0002] With the continuous improvement of the medical level, the average life expectancy has been extended accordingly, and the aging process of my country's population has accelerated. At the same time, the rapid development of my country's economy has also led to an increase in the number of migrant workers year by year, and the personal safety of the left-behind elderly has become a hot social issue. [0003] Due to the decline in the physical function of the elderly, most of them suffer from cardiovascular diseases, osteoporosis and other symptoms, which increases the chance of the elderly falling. Falling will not only cause physical damage to the elderly, but also cause the onset of other diseases. If the elderly cannot be rescued in time afte...

AI Technical Summary

Problems solved by technology

This solution has many limitations such as forgetting to wear it, fixed wearing position and battery life.

The environmental solution deploys a multi-sensor network in the user's living environment, and uses environmental parameters such as sound and vibration to judge whether a person has fallen. Although compared with the wearable solution, the user does not need to wear it, but the living environment needs to be modified , and the system composition is complex and the cost is high

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