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Neural network for pedestrian re recognition and pedestrian re-recognition algorithm based on deep learning

A pedestrian re-identification and neural network technology, applied in the field of pedestrian re-recognition algorithms, can solve problems such as large pose changes, increase the difficulty of pedestrians, and complex perspective changes, and achieve the goal of reducing the misrecognition rate, improving the correct recognition rate, and robust pedestrian characteristics. The effect of matching ability

Active Publication Date: 2018-02-23
PEKING UNIV
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Problems solved by technology

However, there are usually large pose changes and complex viewing angle changes between different images of pedestrians acquired by different cameras, which greatly increases the difficulty of pedestrian re-identification algorithms to match pedestrians

Method used

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  • Neural network for pedestrian re recognition and pedestrian re-recognition algorithm based on deep learning
  • Neural network for pedestrian re recognition and pedestrian re-recognition algorithm based on deep learning
  • Neural network for pedestrian re recognition and pedestrian re-recognition algorithm based on deep learning

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Embodiment Construction

[0029] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0030] figure 1 A conceptual schematic diagram of a first neural network 100 for pedestrian re-identification according to an embodiment of the present invention is shown.

[0031] Such as figure 1 As shown, the first neural network 100 for pedestrian re-identification includes a first neural network 101 and a second neural network 103 .

[0032] Such as figure 1 As shown, the first neural network 101 uses the original full-body...

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Abstract

The invention discloses a neural network for pedestrian re recognition and a pedestrian re-recognition algorithm based on deep learning. The neural network comprises a first neural network that uses an original full-body image of a pedestrian as a first input and outputs a first identification feature and a second neural network that uses an affine transformation image of a body part image extracted from the original full-body image of the pedestrian as a second input and outputs a second identification feature. The body parts at least include a head, a trunk, and arms and legs; and the firstidentification feature and the second identification feature are combined into an overall identification feature. Therefore, the pedestrian feature matching capability with the high robustness is realized; and thus the correct recognition rate is improved and / or the false recognition rate is reduced.

Description

technical field [0001] The invention relates to the fields of convolutional neural networks and image recognition. More specifically, the present invention relates to a neural network for pedestrian re-identification and a pedestrian re-identification algorithm based on deep learning. Background technique [0002] With the popularity of video surveillance technology, the role of pedestrian re-identification technology has become increasingly important, it can help people automatically complete the task of searching for specific people from massive image or video data. [0003] The use of convolutional neural networks for feature extraction and feature matching are two important components of person re-identification technology. However, there are usually large pose changes and complex viewing angle changes between different images of pedestrians acquired by different cameras, which greatly increases the difficulty of pedestrian re-identification algorithms to match pedestri...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06T3/00
CPCG06V40/103G06N3/045G06F18/214G06T3/147
Inventor 张史梁田奇高文李佳宁苏驰
Owner PEKING UNIV
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