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Single-stage video behavior detection method

A detection method, a single-stage technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as joint training, unfavorable behavior detection model coordination and joint optimization, and affecting algorithm calculation efficiency, etc., to improve The effect of efficiency, simplified network structure, and high detection performance

Active Publication Date: 2018-11-13
UNIV OF SCI & TECH OF CHINA
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Problems solved by technology

[0005] However, the above multi-stage method regards feature extraction, sliding window nomination, and behavior classification as independent processing stages, and each stage cannot be jointly trained, which is not c

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Embodiment Construction

[0017] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0018] In order to solve the problems of existing video behavior detection methods such as complex structure, low detection accuracy, and slow processing speed, the embodiment of the present invention provides a single-stage video behavior detection method; first, in order to improve computing efficiency, the method of the present invention encapsulates all calculations Into a network, the action detection task is performed in a single-stage convolu...

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Abstract

The invention discloses a single-stage video behavior detection method. The method comprises the following steps: constructing a multi-scale behavior fragment regression network based on a convolutional neural network at a training stage; taking a training video and a frame-level real behavior label as inputs, and training the multi-scale behavior fragment regression network with an end-to-end optimization method of multi-task learning to obtain a well-trained multi-scale behavior fragment regression network model; when a new video is input at a use stage, generating an input frame sequence with the same length as the training video by a time dimension sliding window, and predicting the behavior category of the input frame sequence and a corresponding time position with the trained multi-scale behavior fragment regression network mode; and processing a prediction result by non-maximum suppression to produce a final behavior detection result. Through adoption of the method, the detection performance and detection efficiency can be improved.

Description

technical field [0001] The invention relates to the technical field of video behavior detection, in particular to a single-stage video behavior detection method. Background technique [0002] In recent years, video shooting equipment (such as smart phones, digital cameras, surveillance cameras, etc.) important information carrier. With the increasing demand for computer intelligence and the rapid development of pattern recognition technology, image processing technology and artificial intelligence technology, there is a huge practical demand and high commercial value for using computer vision technology to analyze video content. Human activities are often the main body of information in videos, and the detection of human activities in videos is of great significance for video understanding. The video human behavior detection task is to detect the category of each human behavior instance contained in the video and locate the occurrence time of each behavior instance in the ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/20G06F18/214
Inventor 王子磊刘志康
Owner UNIV OF SCI & TECH OF CHINA
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