Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method

With the involution of pedestrian detection technology, higher requirements are put forward for the detection accuracy under the conditions of insufficient light, target occlusion, and too small scale. Without information and multiscale pedestrian target, visible light single-mode pedestrian detecti...

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Main Authors: Duo Pan, Xuemei Zhou
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2022/8940743
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author Duo Pan
Xuemei Zhou
author_facet Duo Pan
Xuemei Zhou
author_sort Duo Pan
collection DOAJ
description With the involution of pedestrian detection technology, higher requirements are put forward for the detection accuracy under the conditions of insufficient light, target occlusion, and too small scale. Without information and multiscale pedestrian target, visible light single-mode pedestrian detection algorithm has poor performance. To solve the above problems, a pedestrian detection algorithm combining attention mechanism and nonmaximum suppression method is proposed in this study, aiming to improve the accuracy of pedestrian detection. In addition, residual network ResNet-50 and IoU (intersection over union) loss function are also adopted to improve pedestrian detection accuracy. Attention mechanism was used to optimize and highlight pedestrian area features, and meanwhile, the nonmaximum suppression method was applied to improve the robustness of the algorithm. Experimental results show that the detection accuracy of the proposed algorithm is significantly higher than that of the traditional convolutional neural network algorithm.
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institution Kabale University
issn 1687-5699
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Advances in Multimedia
spelling doaj-art-51545a5818674bbdb915d2f3893333712025-02-03T01:12:21ZengWileyAdvances in Multimedia1687-56992022-01-01202210.1155/2022/8940743Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression MethodDuo Pan0Xuemei Zhou1College of Intelligent Manufacturing and Information EngineeringCollege of Intelligent Manufacturing and Information EngineeringWith the involution of pedestrian detection technology, higher requirements are put forward for the detection accuracy under the conditions of insufficient light, target occlusion, and too small scale. Without information and multiscale pedestrian target, visible light single-mode pedestrian detection algorithm has poor performance. To solve the above problems, a pedestrian detection algorithm combining attention mechanism and nonmaximum suppression method is proposed in this study, aiming to improve the accuracy of pedestrian detection. In addition, residual network ResNet-50 and IoU (intersection over union) loss function are also adopted to improve pedestrian detection accuracy. Attention mechanism was used to optimize and highlight pedestrian area features, and meanwhile, the nonmaximum suppression method was applied to improve the robustness of the algorithm. Experimental results show that the detection accuracy of the proposed algorithm is significantly higher than that of the traditional convolutional neural network algorithm.http://dx.doi.org/10.1155/2022/8940743
spellingShingle Duo Pan
Xuemei Zhou
Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method
Advances in Multimedia
title Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method
title_full Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method
title_fullStr Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method
title_full_unstemmed Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method
title_short Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method
title_sort pedestrian detection algorithm combining attention mechanism and nonmaximum suppression method
url http://dx.doi.org/10.1155/2022/8940743
work_keys_str_mv AT duopan pedestriandetectionalgorithmcombiningattentionmechanismandnonmaximumsuppressionmethod
AT xuemeizhou pedestriandetectionalgorithmcombiningattentionmechanismandnonmaximumsuppressionmethod