The present invention relates to the technical field of image identification, particularly relates to a deep network system and behavior identification method represented on the basis of a Lie group skeleton, and specifically relates to a behavior identification method and apparatus based on deep network technology, and a storage medium, wherein the deep network system comprises a logarithm mapping layer, an excitation layer, a first complete connection layer, a time information learning layer, etc. From original deep skeleton data, extracted Lie group skeleton features are input into a CNN network designed for a Lie group, and transformed Lie-algebra features are input into a Bi-LSTM network (the time information leanring layer) before the complete connection layer; and then, prediction labels and scores from softmax layers (output layers) of the two networks are merged so as to effectively identify a behavior.
BEHAVIOR IDENTIFICATION METHOD AND APPARATUS BASED ON DEEP NETWORK TECHNOLOGY, AND STORAGE MEDIUM