Embedded platform real-time tumble detection method based on improved attitude estimation algorithm

Abstract

The invention relates to an embedded platform real-time tumble detection method based on an improved attitude estimation algorithm. According to the method, an attitude estimation network is established by using depth separable convolution, an attention mechanism and an inverse residual error structure and is used for fall detection. The precision of the attitude estimation network is further improved; the parameter quantity and the calculation quantity are greatly reduced; the distance of each articulation point of the human body between different video frames is calculated to track the humanbody; acceleration of human body articulation points is calculated by using front and rear video frames, and whether falling occurs is judged according to the acceleration, the relative positions ofthe articulation points and the like, so that the attitude estimation network is more suitable for being deployed on an embedded platform, and a real-time effect can be achieved by deploying on a TX2embedded platform. According to the method, human body tracking is carried out by using multi-person human body joint point coordinates and skeleton information obtained in front and back frames, posture estimation is more stable due to multi-person tracking, and the problem of fall detection in a multi-person scene can be better solved.

Description

technical field [0001] The invention belongs to the technical field of computer vision, in particular to an embedded platform real-time fall detection method based on an improved attitude estimation algorithm. Background technique [0002] With the improvement of medical conditions and the improvement of living standards, the average life expectancy of the population has increased significantly, which has accelerated the process of population aging. Population aging has brought many social problems, and reducing the losses caused by accidents of the elderly is an urgent problem to be solved. According to the WHO report, an estimated 646,000 people worldwide die each year due to falls without timely treatment, among which the elderly account for the largest proportion. Among the current fall detection methods for the elderly, the method based on wearable devices has relatively large limitations and high cost; although the computer vision fall detection algorithm based on pos...

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Problems solved by technology

[0004] In view of the shortcomings of the current attitude estimation algorithm, such as too large model, too many parameters, and no tracking of the human body during actual deployment, the present invention proposes a real-time fall detection method for embedded platforms based on the improved attitude estimation algorithm, and reduces the model by improving the network structure. Size, to complete the real-time estimation of human posture on the embedded platform and the purpose of detecting human falls

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