检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:艾青林[1] 杨佳豪 崔景瑞 AI Qing-lin;YANG Jia-hao;CUI Jing-rui(Key Laboratory of Special Purpose Equipment and Advanced Manufacturing Technology,Ministry of Education and Zhejiang Province,Zhejiang University of Technology,Hangzhou 310023,China)
机构地区:[1]浙江工业大学特种装备制造与先进加工技术教育部/浙江省重点实验室,浙江杭州310023
出 处:《浙江大学学报(工学版)》2023年第10期1933-1944,1976,共13页Journal of Zhejiang University:Engineering Science
基 金:国家自然科学基金资助项目(52075488);浙江省自然科学基金资助项目(LY20E050023).
摘 要:针对当前规模的小目标行人数据集较少,传统行人检测模型对小目标检测效果较差的问题,提出一种基于消隐点性质,提出自适应增殖数据增强和全局上下文特征融合的小目标行人检测方法.利用射影几何与消隐点的性质,对图像中的多个目标进行复制;通过仿射变换投影到新的位置,生成多个大小与背景合理的小目标样本以完成数据增强.利用跨阶段局部网络与轻量化操作改进沙漏结构,融合坐标注意力机制强化骨干网络.设计全局特征融合颈部网络(GFF-neck),以融合全局特征.实验表明,在经过数据增强后的WiderPerson数据集上,改进算法对行人类别的检测AP值达到了79.6%,在VOC数据集上mAP值达到了80.2%.测试结果表明,当搭建实验测试系统进行实景测试时,所提算法有效提升了小目标行人检测识别精度,并满足实时性要求.A global context feature fusion method for small target pedestrian detection was proposed based on the property of vanishing points and adaptive data augmentation to address the issues of limited small-scale pedestrian datasets and poor detection performance of traditional pedestrian detection models.Multiple targets in the image were copied by using the properties of projective geometry and vanishing points.The targets were projected to new locations through Affine transformation.Multiple small target samples with reasonable size and background were generated to complete data enhancement.The cross stage local network and lightweight operation were used to improve the hourglass structure,and the coordinate attention mechanism was integrated to strengthen the backbone network.The global feature fusion neck network(GFF-neck)was designed to fuse the global features.The experimental results showed that the improved algorithm achieved a detection AP value of 79.6%for pedestrian categories on the data enhanced WiderPerson dataset,and an mAP value of 80.2%on the VOC dataset.An experimental test system was built to test the real scene.The test results show that the proposed algorithm effectively improves the accuracy of small target pedestrian detection and recognition and meets the real-time requirements of the test.
关 键 词:消隐点 数据增强 全局特征融合 小目标行人检测 轻量化沙漏结构
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.198