Pedestrian re-identification method and device based on semi-supervised training mode and medium

A pedestrian re-identification and training method technology, applied to devices and storage media, in the field of pedestrian re-identification methods based on semi-supervised training methods, can solve the problems of single feature selection and affect the recognition accuracy, and achieve accurate recognition.

Active Publication Date: 2019-12-10
XIAMEN MEIYA PICO INFORMATION
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Problems solved by technology

[0004] In the current pedestrian re-identification, due to the single feature selection, t...

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  • Pedestrian re-identification method and device based on semi-supervised training mode and medium
  • Pedestrian re-identification method and device based on semi-supervised training mode and medium
  • Pedestrian re-identification method and device based on semi-supervised training mode and medium

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Embodiment Construction

[0054]The application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0055] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0056] figure 1 A method for re-identifying pedestrians based on a semi-supervised training method of the present invention is shown, the method includes:

[0057] The training sample set generation step S101 is to use the collected target domain sample set and open source d...

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Abstract

The invention provides a pedestrian re-identification method and device based on a semi-supervised training mode and a storage medium. The method comprises the following steps: constructing a trainingsample set by using the collected target domain sample set and open source data set based on a semi-supervised training mode; and training a deep residual network by using the training sample set toobtain a trained deep residual network model, identifying the acquired pedestrian images by using the trained deep residual network model to obtain feature values of the pedestrian images, and determining whether the pedestrian images belong to the same person according to cosine distances among the feature values. According to the invention, the virtual sample is generated; a smoothing function is constructed when a virtual sample is generated; and meanwhile, a DBSCAN clustering algorithm is used for adding pseudo tags to the virtual samples, local features and global features are used in thedeep neural network, and a joint loss function of different weight combinations is adopted, so that the trained deep neural network is accurate and more reliable in recognition.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a pedestrian re-identification method, device and storage medium based on a semi-supervised training method. Background technique [0002] With the advancement of society and technology, face recognition has increasingly become a reliable security technology. However, for most of the current cameras, the resolution often cannot meet the requirements of the face recognition system, so the pedestrian re-identification technology that can be applied to the existing monitoring system is extremely necessary. Person re-identification (Person re-identification) is to use image processing technology to determine whether a pedestrian under a certain camera appears in other cameras, so as to describe the pedestrian's activity path and achieve the purpose of cross-camera tracking. At present, the commonly used methods for person re-identification mainly include representati...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/53G06N3/045G06F18/241G06F18/214
Inventor 林修明吴鸿伟王国威陈志飞林淑强杜新胜
Owner XIAMEN MEIYA PICO INFORMATION
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