A human motion prediction method based on attention mechanism

A technology of human action and prediction method, applied in artificial life, biological neural network models, instruments, etc., can solve problems such as stability and accuracy, and achieve the effect of avoiding information redundancy

Active Publication Date: 2018-12-25
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0012] The purpose of the present invention is to propose a new human body action prediction method in or

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  • A human motion prediction method based on attention mechanism
  • A human motion prediction method based on attention mechanism
  • A human motion prediction method based on attention mechanism

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Embodiment

[0050] A kind of human action prediction method based on attention mechanism, selects Tensorflow to build the attention model that is used for action prediction, comprises the following steps:

[0051] Step 1: According to the instruction, read all the data from the dataset. For example, "eating", iterates through all folders and reads according to the file. In this embodiment, the data set used is the human3.6m data set, so each frame of the read data is divided into 99 float-type values, which are respectively the position information data (three-dimensional) of a root node and the index of 32 parts Map rotation angle.

[0052] Step 2: Standardize the data. First, calculate the standard deviation of all the obtained data according to each column, remove the data with a standard deviation of 0, and obtain all columns with a standard deviation other than 0, subtract each value of each row from the mean value of the column it is in, and then Divide the standard deviation of ...

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Abstract

The invention relates to a human motion prediction method based on attention mechanism, belonging to the technical field of human-computer interaction and virtual reality. The method of the inventionreads all the data from the human body movement posture data set and performs standardization processing, then reads the training data batch according to the generated random number according to the length of the frame needed to be trained in the instruction, inputs the data into the attention model for data processing, and performs motion reconstruction according to the processed data. The invention adopts two kinds of attention mechanisms, namely global attention mechanism and local attention mechanism. Compared with the prior art, the method of the invention can avoid information redundancyin a certain time and distribute attention under a certain window at the same time.

Description

technical field [0001] The invention relates to a human body action prediction method based on an attention mechanism, which belongs to the technical field of human-computer interaction and virtual reality. Background technique [0002] Humans are predictive, able to make accurate short-term predictions about the world around them based on previous events. In the field of virtual reality, human-computer interaction is an important research direction. How to enable machines to imitate human's ability to make corresponding predictions on human actions is currently a research hotspot in this field. [0003] For computers, predicting human motion is important for timely human-computer interaction, obstacle avoidance, and person tracking. While simple physical phenomena, such as the motion of inanimate objects, can be predicted using known laws of physics, there is no simple equation that governs a person's conscious movement. Many everyday problems, such as predicting what an...

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Application Information

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IPC IPC(8): G06N3/04G06N3/00
CPCG06N3/008G06N3/045
Inventor 余月陈相儒田聂豪黄焯恒陈宇峰
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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