Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Pedestrian detection method based on multi-layer convolution feature fusion

A technology of feature fusion and pedestrian detection, which is applied in the field of pedestrian detection, can solve the problems of missed detection of pedestrian detection, achieve the effects of improving detection accuracy, enhancing detection effect, and improving robustness

Pending Publication Date: 2021-03-16
JIANGSU UNIV OF SCI & TECH
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a pedestrian detection method of multi-layer convolution feature fusion to solve the problem of missed detection in pedestrian detection of different scales in the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Pedestrian detection method based on multi-layer convolution feature fusion
  • Pedestrian detection method based on multi-layer convolution feature fusion
  • Pedestrian detection method based on multi-layer convolution feature fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0043] figure 1 It is a flowchart of a pedestrian detection method for multi-layer convolution feature fusion in the present invention, figure 2 The feature extraction network Darket-61 structure of the present invention, image 3 It is the network structure of YOLOv3 of the present invention, Figure 4 It is a schematic diagram of the structure of the FP...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a pedestrian detection method based on multi-layer convolution feature fusion, and the method comprises the steps: constructing a new feature extraction network Darknet-61 through the reconstruction of a residual network, enabling the feature extraction network Darknet-61 to have the capability of six times of down-sampling, and increasing the output of a YOLO output layerof a YOLOv3 algorithm from 3 layers to 5 layers through the new feature extraction network Darknet-61; subsequently, obtaining a target candidate box on the basis of a YOLOv3 algorithm with five-layeroutput through a k-mean algorithm, and carrying out subsequent processing on the current optimal candidate box in the target candidate box through an NMS method. According to the method, the Darknet-53 feature extraction network is improved, four residual networks and convolution layers are introduced, the down-sampling frequency is increased, a 7 * 7 feature map is output, the characterization capability of low-layer features is enhanced, and the precision of large-scale pedestrian detection is improved.

Description

technical field [0001] The invention relates to the field of pedestrian detection, in particular to a pedestrian detection method for multi-layer convolution feature fusion. Background technique [0002] Pedestrian detection, as a core technology of smart devices, enables machines and devices to obtain surrounding video or image information, and uses the powerful analysis capabilities of computers to visually process the acquired information, so that they can observe and understand complex things like humans. ability to analyze. Help people complete various recognition and detection tasks. [0003] Pedestrian detection is an important research direction in the field of computer vision. The computer recognizes whether there are pedestrians from images or video clips. If there are pedestrians, it further detects the specific location of pedestrians, so as to accurately calibrate their position coordinates. Among them It is widely used in manufacturing, military, medical and ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06N3/045G06F18/23213G06F18/253
Inventor 马国军韩松夏健郑威
Owner JIANGSU UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products