LRCN network-based behavior identification method and apparatus, device and medium

Abstract

The embodiment of the invention provides an LRCN network-based behavior identification method and apparatus, a device and a medium, wherein the method comprises the steps of obtaining a to-be-identified video frame sequence and a corresponding optical flow graph; inputting the video frame sequence to be identified and the corresponding optical flow graph into a long-time recursion convolutional network model; obtaining a behavior category label of the to-be-identified video frame sequence; inputting each adjacent preset number of frames in the to-be-identified video frame sequence into a first convolutional neural network in a long-time recursive convolutional network model, and inputting the optical flow graph corresponding to the preset number of frames into a second convolutional neural network in the long-time recursive convolutional network model, wherein the convolutional neural network performs convolutional layer sharing on the preset number of frames and the optical flow graph in a data fusion manner. According to the scheme, sharing is introduced between the convolutional layers, so that the behavior recognition is performed after a large amount of redundancy of image information between adjacent frames is reduced, and the overall calculation amount of the network is reduced.

Description

technical field [0001] The present invention relates to the technical field of behavior recognition, in particular to a behavior recognition method, device, equipment and readable storage medium based on LRCN (Long-term Recursive Convolutional Network) network. Background technique [0002] Behavior recognition is another specific example of the sequence learning task, which is a kind of learning with time-series image sequences as input. The purpose of behavior recognition is to identify the behavior of one or more agents from a series of observations of the behavior of the agent and the state of the environment. Since the 1980s, this research area has attracted the attention of many people in computer science due to its many different applications and its relevance to many different fields of study, for example, medicine, human-computer interaction, and sociology. [0003] Currently, the LRCN (Long-term Recurrent Convolutional Network) network combining Convolutional Neur...

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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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