Behavior recognition method, device, equipment and medium based on lrcn network

Abstract

Embodiments of the present invention provide a behavior recognition method, device, device, and readable storage medium based on an LRCN network, wherein the method includes: acquiring a video frame sequence to be recognized and a corresponding optical flow graph; The sequence and the corresponding optical flow graph are input into the long-term recursive convolutional network model to obtain the behavior category label of the video frame sequence to be identified, and each adjacent preset number of frames in the video frame sequence to be identified is input In the first convolutional neural network in the long-term recursive convolutional network model, input the optical flow graph corresponding to the preset number of frames into the second convolutional neural network in the long-term recurrent convolutional network model, the convolutional neural network Convolutional layer sharing is performed by data fusion for a preset number of frames and optical flow maps respectively. This scheme introduces sharing between convolutional layers, which reduces the large amount of redundancy in the image information between adjacent frames before performing behavior recognition, thereby helping to reduce the overall computational load of the network.

Description

Technical field [0001] The present invention relates to the field of behavior identification, and in particular, to a behavior identification method, apparatus, device, and readable storage medium based on an LRCN (long recursive web) network. Background technique [0002] Behavior identifies another specific example of the sequence learning task, which is the image sequence of the timing as an input. The purpose of behavioral identification is to identify one or more agents from a series of observations of agents and environmental conditions. Since the 1980s, this research area has attracted the attention of many computer sciences in many different applications and associations with many different research sectors, such as medical, human-computer interaction and sociology. [0003] Currently, the LRCN (CNN) of conjunctive neural network (CNN) and the circulating neural network (LSTM) network is currently applied to video sequences for behavioral recognition. Identification metho...

AI Technical Summary

Problems solved by technology

[0007] The embodiment of the present invention provides a behavior recognition method based on LRCN (Long-term Recursive Convolutional Network) network to solve the technical problem of large computational overhead in the prior art when performing behavior recognition based on LRCN network

[0009] The embodiment of the present invention also provides a behavior recognition device based on the LRCN network to solve the technical problem of large computational overhead in the prior art when performing behavior recognition based on the LRCN network

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