Real-time pedestrian detection method and system based on deep learning

A pedestrian detection and deep learning technology, applied in instruments, biological neural network models, computing, etc., can solve problems such as slow detection speed

Active Publication Date: 2020-01-24
WUHAN UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem of slow detection speed of existing pedestrian detection methods, the present invention proposes a real-time pedestrian detection method and system based on deep learning, and achieves the effect of real-time detection by improving the network structure

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  • Real-time pedestrian detection method and system based on deep learning
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  • Real-time pedestrian detection method and system based on deep learning

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Embodiment Construction

[0035] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0036] please see figure 1 , a kind of real-time pedestrian detection method based on deep learning provided by the present invention comprises the following steps:

[0037] Step 1: Mark pedestrians uniformly on the actual surveillance video data as a training picture; send the training picture to the deep network to extract features, update the network weight parameters after several iterations, and obtain a pedestrian detector with an accuracy higher than the preset threshold ;

[0038] In this embodiment, the actual surveillance video data (resolution 19...

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Abstract

The invention discloses a real-time pedestrian detection method and system based on deep learning, and the method comprises the steps: firstly obtaining video data, carrying out the size adjustment ofan inputted video image, and carrying out the feature extraction of the inputted image through depth separable convolution; performing up-sampling operation on deep features by a passthough layer structure in a network, performing feature fusion on the deep features and shallow features, and then outputting a deep feature map with low resolution and a feature map with high resolution, which fusescoarse-grained features and fine-grained features; and finally, carrying out regression and prediction on the two feature maps with different scales, and outputting a bounding box and confidence of each pedestrian detection result. According to the method, in an actual monitoring scene, the real-time pedestrian detection method based on the high-definition video, which meets the requirements of the real scene, is realized, and the detection efficiency is improved under the condition of ensuring the accuracy.

Description

technical field [0001] The invention belongs to the technical field of computer image recognition, and relates to a real-time pedestrian detection method and system, in particular to a real-time pedestrian detection method and system based on deep learning. Background technique [0002] Pedestrian detection is an important part of target detection, and it is also a research hotspot in computer vision. It is widely used in criminal investigation video surveillance, intelligent driving and specific target retrieval. In recent years, thanks to the continuous development of deep learning, pedestrian detection has made great progress. However, due to the complex structure of the deep network model and the large amount of parameter calculation, the detection speed is greatly reduced. And based on the detection speed of the video sequence, there is a real-time requirement. [0003] Existing object detection methods based on deep learning can be roughly divided into proposal-based...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04
CPCG06V40/10G06V10/40G06N3/045G06F18/241G06F18/214Y02T10/40
Inventor 梁超焦黎王晓胡必成鲁铮叶力果王泽铠
Owner WUHAN UNIV
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