A Neural Network Gait Recognition Method Based on Attention Mechanism
A neural network and gait recognition technology, applied in biological neural network models, neural architecture, character and pattern recognition, etc., can solve the problem of insufficient utilization of attention mechanism information
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment Construction
[0029] The gait recognition method based on the attention mechanism of the present invention uses the CASIA-B gait data set issued by the Chinese Academy of Sciences to conduct experiments. Specifically include the following steps:
[0030] (1) Training a gait feature extraction model based on the attention mechanism.
[0031] 1.1) Split the training set and test set from the benchmark dataset CASIA-B.
[0032] 1.2) The input size of the 3D convolutional neural network is set as B*C*T*H*W, where B represents the batch dimension, C represents the number of channels of the input gait image, and T represents the frame length of the input gait video sequence , H and W are the length and width of each frame of gait video sequence. In this method, the samples are normalized to a size of 64*44.
[0033] 1.3) Through the iterative optimization strategy, the samples and sample labels are used to pre-train the gait feature extraction model, so that the trained gait feature extraction...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


