Hand gesture recognition method using artificial neural network and device thereof

摘要

An embodiment of the present invention relates to an artificial neural network-based hand gesture recognition method and apparatus, and the technical problem to be solved is a real-time learning RCE neural network algorithm and DTW distance measurement to measure similarity by reflecting the characteristics of data changing on a time axis. It is to provide an efficient method and apparatus for recognizing hand gestures combining algorithms. To this end, the present invention extracts feature data from hand gesture input data; And a learning and recognition step of learning and recognizing hand gestures by inputting feature data, wherein the learning and recognition step comprises: feature data input step of sequentially receiving feature data; And a DWT distance measurement step of calculating a distance between the feature data and the neuron center point using a dynamic time warping (DTW) distance measurement algorithm; And a DWT distance measurement step of calculating a distance between the feature data and the neuron center point using a DTW distance measurement algorithm. An activated neuron determination step of determining a neuron having a characteristic inside a radius of the corresponding neuron as an activated neuron; And a gesture recognition step having a neuron label output step of outputting a label of a neuron having a minimum distance value among activated neurons.