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Multi-person behavior detection method and system based on deep learning and fusing various kinds of interaction information

An interactive information and deep learning technology, applied in the field of multi-person behavior detection methods and systems, can solve problems such as utilization, lack of interactive information, and inability to accurately detect interactive behaviors, and achieve the effect of improving accuracy

Active Publication Date: 2020-08-11
SHANGHAI JIAO TONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Its defect is that it only considers the movement changes of a single person inside its bounding box, does not use the interaction information between people and other people or objects, and cannot accurately detect more complex interactive behaviors, such as opening doors, watching TV, and conversations with other people

Method used

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  • Multi-person behavior detection method and system based on deep learning and fusing various kinds of interaction information
  • Multi-person behavior detection method and system based on deep learning and fusing various kinds of interaction information
  • Multi-person behavior detection method and system based on deep learning and fusing various kinds of interaction information

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Embodiment Construction

[0032] This embodiment relates to a multi-person behavior detection system based on deep learning fusion of various interaction information, including: a training sample acquisition module, an object detection module, and a behavior detection network module that integrates multiple interactions, wherein: the sample of the training sample acquisition module And the object detection frame of the object detection module is used as the input of the behavior detection network module. After the behavior detection network is trained, the bounding box area of ​​​​the person and the object is used to obtain the model of the area representation and memory representation of the person and object, and further perform on this representation. Multi-category judgment, the object detection module detects people and objects in the video to be tested, and the behavior detection network module further tests and infers the judgment of each person's behavior in the video based on the detection resul...

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PUM

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Abstract

The invention discloses a multi-person behavior detection method and system based on deep learning fusion of various interaction information. The method comprises the following steps: building a videolibrary with a label as a sample set to train a behavior detection network, processing a to-be-detected video through the trained network, and realizing the detection of an object behavior in a region according to a final output vector. According to the method, the complexity of human behaviors is fully considered, the interaction relationship between the human behaviors and other people, objectsand long-term memory information is integrated while the motion of the human is considered, and the video behavior detection precision is effectively improved.

Description

technical field [0001] The present invention relates to a technology in the field of artificial intelligence video recognition, in particular to a multi-person behavior detection method and system based on deep learning and fusion of various interactive information. Background technique [0002] The goal of computer vision is to use computer programs to handle various visual tasks, often involving multimedia such as images and videos. Convolutional neural network is a deep learning technique widely used in computer vision tasks. It obtains more general deep robust representations by training filter parameters in image convolution operations. These representations are in the form of high-dimensional vectors. Or matrix, which can be used for behavior detection or classification, that is, to detect the position of people appearing in the video and judge their respective behaviors. [0003] The existing behavior detection technology generally detects the bounding box of the per...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V40/103G06N3/047G06N3/045G06F18/241G06F18/2415Y02D10/00
Inventor 汤佳俊夏锦牟芯志庞博卢策吾
Owner SHANGHAI JIAO TONG UNIV
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