A Method for Analyzing Ski Movement Sequence Based on Hidden Markov

Abstract

The invention discloses a method for analyzing skiing motion sequences based on Hidden Markov, which belongs to the field of motion posture data processing and analysis. The realization method of the present invention is: by windowing the original attitude data of the skier collected by the sensor, dividing the original attitude data into data frames on a time series, and then using SVD and matrix norm to extract the "symbolic value" representing the attitude matrix . Based on Hidden Markov, the probability transition model of the skiing motion sequence is built, and the parameters of the probability transition model of the skiing motion sequence are optimized by using the "symbolic value" sequence on the time series, and the optimal path of the hidden state of the skiing motion sequence is calculated. Calculate the probability of each skiing state at the next moment by calculating the optimal hidden state path and the probability transition model, and then predict the skiing state at the next moment. Improve the training effect for ski trainers.

Description

technical field [0001] The invention relates to a method for analyzing skiing motion sequences based on Hidden Markov, and belongs to the field of motion posture data processing and analysis. Background technique [0002] The 24th Winter Olympic Games will be held in my country in 2022, and people's enthusiasm for ice and snow sports continues to rise. Whether it is an amateur or a professional athlete, it is necessary to obtain the action sequence during the skiing process during training, so as to analyze and guide their skiing process. The most important technology in the field of obtaining human motion posture sequences is motion capture technology. Many scholars at home and abroad have conducted a lot of research on obtaining human body motion posture sequences using existing motion capture technologies. The current mainstream motion capture methods are divided into There are three kinds of photoelectric capture, image capture and inertial sensor capture. In the field...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a kind of method based on Hidden Markov analysis ski motion sequence, can solve following technical problem: (1) reduce the dimension of attitude matrix by using SVD singular value decomposition and matrix norm, and then pass low dimension The data represents the attitude information, reducing the amount of calculation; (2) building the probability transition model of the skiing sequence with the help of the hidden Markov method; (3) optimizing the parameters of the skiing sequence model through the observation state; (4) using the obtained skiing sequence The probability transition model analyzes the motion sequence to realize the analysis of the athlete's skiing process

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