计算机工程2024，Vol.50Issue(3)：290-297,8.DOI:10.19678/j.issn.1000-3428.0066951
基于注意力机制的多尺度融合人群计数算法
Multiscale Fusion Crowd Counting Algorithm Based on Attention Mechanism
摘要
Abstract
A multiscale fusion crowd counting algorithm based on attention mechanism is proposed to addresses the issues of large head scale changes and high background noise in crowd counting images,fully aggregating multiscale information to effectively distinguish background noise.Atrous spatial pyramid pooling based on residual connection method is constructed to capture multiscale head target features while incorporating spatial details from shallow feature maps through residual structures and multiple dilated convolutions with different expansion rates,thereby improving the quality of feature maps.A cross-layer multiscale feature fusion module is built to integrate edge details and contextual semantic information of different sizes of shallow and deep branches.In addition,a feature fusion module based on multi-branch is designed to integrate multiscale information of different receptive field sizes,thereby alleviating the problem of large-scale head scale changes.A channel and spatial attention mechanism module is further constructed based on the matrix similarity operation to extract pixel level feature weights,enhance the network's discriminative ability for background and head targets,and adaptively correct position information.The experimental results show that compared to the optimal values of the 11 comparison algorithms,the proposed algorithm reduces the Mean Absolute Error(MAE)and Root Mean Square Error(RMSE)indicators by 1.4%and 4.2%on the SHA dataset,and reduced by 4.9%and 1.8%on the UCF_CC_50 dataset,the proposed algorithm can accurately predict the distribution status,estimate the number of people,and generate high-quality population density maps.关键词
人群计数/多尺度融合/注意力机制/卷积神经网络/密度图Key words
crowd counting/multiscale fusion/attention mechanism/Convolutional Neural Network(CNN)/density map分类
信息技术与安全科学引用本文复制引用
谢新林,尹东旭,张涛源,谢刚..基于注意力机制的多尺度融合人群计数算法[J].计算机工程,2024,50(3):290-297,8.基金项目
国家自然科学基金(62006169) （62006169）
山西省重点研发计划(202202010101005) （202202010101005）
太原科技大学博士科研启动基金(20192047) （20192047）
山西省高等学校科技创新项目(2020L0347). （2020L0347）
