A Bone Jitter Detection Method Based on Dynamic Weighting and Gray Prediction
A technology of gray prediction and detection method, applied in the field of human-computer interaction, can solve the problems of low detection accuracy and slow processing speed, and achieve the effect of strengthening regularity, improving accuracy, and reducing time and space complexity.
Active Publication Date: 2022-02-22
NANJING UNIV OF POSTS & TELECOMM
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[0004] The purpose of the present invention is to solve the problems of slow processing speed and low detection accuracy in the prior art, and to provide a bone shaking detection method based on dynamic weighting and gray prediction. Data information, find out the number of data that can have the characteristics of the data sequence through data preprocessing, and perform secondary processing on the data through the piecewise power series algorithm so that the data can have strong regularity
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[0032] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.
[0033] In the embodiment of the present invention, a bone shake detection method based on dynamic weighting and gray prediction is provided, which performs dynamic identification processing on the historical motion data collected by the bone sensor; Initialize the process to preliminarily determine whether bone shaking occurs; finally, integrate the historical motion data through the gray prediction algorithm, extract the features of the historical motion data, and predict the human bone motion in 1s to 2s after the bone based on the acquired features, and judge whether the bone is Jitter occurs.
[0034] refer to figure 1 and figure 2 , the bone shaking detection method b...
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The invention discloses a bone shaking detection method based on dynamic weighting and gray prediction. An effective data sequence corresponding to the skeletal action; performing dynamic weighting processing on the effective data sequence by using a piecewise power function to obtain the weighted data sequence, and obtaining the first regularity of the corresponding skeletal action based on the weighted data sequence; using The grayscale prediction algorithm integrates the weighted data sequence, obtains the second regularity corresponding to the weighted data sequence, and predicts the motion data of the skeleton after 1s to 2s based on the second regularity; sets the bone motion corresponding to the human body motion based on the historical motion data The threshold preprocesses the motion data again to obtain the data sequence {Y m}, Y m =Y i , 0≤i≤m, if it means that the bone performs the next bone action; otherwise, it means that the bone shakes; the present invention can effectively improve the detection efficiency and accuracy of the bone action.
Description
technical field [0001] The invention belongs to the technical field of human-computer interaction, and in particular relates to a bone shaking detection method based on dynamic weighting and gray prediction. Background technique [0002] At present, human-computer interaction technology is becoming more and more mature. In the early days, Microsoft launched Kinect, and the motion sensor manufacturer Leap also launched leap motion, and then VR equipment also developed rapidly. All kinds of human-computer interaction are possible, but because the actions set by the software have their response thresholds. The human body cannot maintain a certain posture for a long time, which leads to the problem of bone shaking. Based on this phenomenon, the bone shake detection method is also produced. [0003] There are also many solutions to bone shaking at home and abroad. Specifically, it can be divided into two categories: setting filters and smoothing data. The first type of settin...
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IPC IPC(8): G06F3/01G06V40/20
CPCG06F3/011G06V40/20
Inventor 王海学杨淑婷楼容张阳刘峰
Owner NANJING UNIV OF POSTS & TELECOMM