A pedestrian rerecognition method based on a fusion convolution neural network

A convolutional neural network and pedestrian technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as no fusion, insufficient mining of overall and local features of pedestrian images, and improve the accuracy rate Effect

Active Publication Date: 2018-12-18
陕西钛极浈清科技有限公司
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Problems solved by technology

[0004] The purpose of the present invention is to solve the technical problem that the overall features and local features of pedestrian images are not fully

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  • A pedestrian rerecognition method based on a fusion convolution neural network
  • A pedestrian rerecognition method based on a fusion convolution neural network
  • A pedestrian rerecognition method based on a fusion convolution neural network

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[0048] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are exemplary only, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

[0049] figure 1 It is a flowchart of a pedestrian re-identification method based on a fusion convolutional neural network according to an embodiment of the present invention. figure 1 As an example to illustrate some specific implementation processes of the present invention, such as figure 1 As shown, the described pedestrian re-identification method based on fusion convolutional neural network comprises the following ...

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Abstract

The embodiment of the invention discloses a pedestrian rerecognition method based on a fusion convolution neural network. The method comprises the steps of: constructing a fusion convolution neural network; preprocessing training pedestrian images and obtaining the convolutional activation map by inputting the images into the fusion convolutional neural network; obtaining the whole feature of thetraining pedestrian image by performing the whole pooling, and obtaining the local feature by performing the local horizontal pooling; learning and optimizing the whole feature and local feature respectively, and training the fused convolution neural network; after preprocessing the test pedestrian images, inputting the image to the fusion convolution neural network, and extracting the whole feature and local feature of the test pedestrian image to obtain the final feature; obtaining the pedestrian recognition results by searching for the pedestrian image matching the final feature in the testset as the target image. The invention makes full use of the advantages of the convolution neural network, learns the whole feature and the local feature of the pedestrian image, and finally fuses the two features to represent the pedestrian image, thereby further improving the matching accuracy of the pedestrian recognition.

Description

technical field [0001] The invention belongs to the fields of pattern recognition and artificial intelligence, and in particular relates to a pedestrian re-identification method based on a fusion convolutional neural network. Background technique [0002] In order to maintain public order and safety and create a safe living environment for people, surveillance cameras are installed in many public places, which can effectively locate target pedestrians and arrest criminal suspects in time. However, in the face of a large amount of data, the human eye can no longer effectively and quickly identify and locate targets. People hope to use computers to solve this problem. The development of person re-identification (Person Re-Identification) has made up for this vacancy in time. Effective person re-identification technology can quickly and accurately search for target pedestrians. However, due to the changing camera shooting angle, light intensity, human posture, etc., this techn...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06N3/045
Inventor 张重司统振刘爽
Owner 陕西钛极浈清科技有限公司
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