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Rapid pedestrian detection method and system

A pedestrian detection and pedestrian technology, applied in the field of target detection and computer vision, can solve the problems of incompatibility between accuracy and detection efficiency, and achieve the effect of improving pedestrian detection speed, reducing false detection rate, and improving discrimination

Pending Publication Date: 2020-05-22
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The present invention provides a fast pedestrian detection method and system to solve the incompatibility between the accuracy and detection efficiency of existing pedestrian detection methods and systems, which has become a technical problem to be solved urgently by those skilled in the art

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Embodiment 1

[0037] Such as Figure 4 As shown, the present invention discloses a fast pedestrian detection method, comprising the following steps:

[0038] Merging the MobileNet network and the RPN network to obtain a MobileNet-RPN detection model, the MobileNet-RPN detection model takes the image to be detected as input, and the predicted pedestrian frame on the image to be detected is output;

[0039] Obtaining a training data set comprising a pedestrian image marked with a real pedestrian border and a background image without pedestrians to train the MobileNet-RPN detection model to obtain a trained MobileNet-RPN detection model;

[0040] Input the image to be detected into the MobileNet-RPN detection model to obtain the predicted pedestrian frame of the image to be detected.

[0041] A fast pedestrian detection method provided by the present invention uses the MobileNet algorithm with fewer parameters to construct a lightweight feature selection network, so that the calculation amoun...

Embodiment 2

[0043] Embodiment 2 is an extended embodiment of Embodiment 1, specifically including the following:

[0044] The present invention is realized based on the deep learning open source framework Pytorch (Facebook's official deep learning framework).

[0045] S11: Using a good classification network for transfer learning and using target detection to extract image features has become the mainstream method based on deep learning in target detection. The commonly used network is VGG (Visual Geometry Group Network, Visual Geometry Group Network, Visual Geometry Group Network) and ZF-Net (deep neural network, champion of 2013 ImageNet classification task) network, however, the parameters of these two networks are extremely large, although they can extract features with strong discriminative power, they will cause the model to propagate forward The amount of calculation is too large, which makes the detection speed of the network extremely slow and cannot be applied in practice.

[0...

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Abstract

The invention discloses a rapid pedestrian detection method and system. The method comprises the steps that a MobileNet network and an RPN network are assembled, a MobileNet-RPN detection model is constructed, and the MobileNet-RPN detection model takes an image to be detected as an input and takes a predicted pedestrian frame on the image to be detected as an output; a training data set includinga pedestrian image marked with a real pedestrian frame and a background image without a pedestrian are obtained, and the MobileNet-RPN detection model trained to obtain a trained MobileNet-RPN detection model; and a to-be-detected image is input into the MobileNet-RPN detection model to obtain a predicted pedestrian frame of the to-be-detected image. Compared with the prior art, a lightweight feature selection network is constructed by using a MobileNet algorithm with less parameter quantity, so that the calculated amount of forward propagation of the network is small, and the speed is high and can reach 44FPS. Therefore, the pedestrian detection speed based on the deep learning method is greatly improved.

Description

technical field [0001] The invention relates to the technical field of target detection in the field of computer vision, in particular to a fast pedestrian detection method and system. Background technique [0002] Visual information is an important source for human beings to perceive the world. Studies have shown that about 80% to 90% of the information that humans obtain from the outside world comes from visual information. Human beings can quickly analyze the perceived information and locate and identify all the objects in it. The ultimate goal of computer vision technology is to enable computers to quickly locate, identify, and analyze targets like humans. Once a computer has the visual recognition ability of humans, it can replace manpower in many fields, thereby greatly saving labor costs and production costs. [0003] Target detection is an important branch of computer vision. Its purpose is to accurately locate and classify targets in images. Pedestrian detection, a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V40/10G06N3/045G06F18/241G06F18/214
Inventor 陈志文陈卓彭涛阳春华
Owner CENT SOUTH UNIV