期刊文献+

结合特征图谱学习的人数统计方法 被引量:2

People counting method combined with feature map learning
下载PDF
导出
摘要 针对实际公共场景视频的人数统计中存在的背景干扰、光照变化、目标间遮挡等问题,提出一种结合特征图谱学习和一阶动态线性回归的人数统计方法。首先,建立图像的尺度不变特征变换(SIFT)特征与目标真实密度图之间的特征图谱映射模型,利用SIFT特征和前述映射模型得到包含目标和背景特征量的特征图谱;然后,根据通常监控视频中背景变化较小、特征图谱中的背景特征量相对稳定的特点,由特征图谱的积分与真实人数通过一阶动态线性回归建立人数回归模型;最后,通过该回归模型模型得出估计人数。在数据集MALL和PETS2009上进行实验,实验结果表明:与累积属性空间方法相比,所提方法平均绝对误差降低了2. 2%;与基于角点检测的一阶动态线性回归方法相比,其平均绝对误差降低了6. 5%,平均相对误差降低了2. 3%。 In order to solve the problems such as background interference,illumination variation and occlusion between targets in people counting of actual public scene videos,a new people counting method combined with feature map learning and first-order dynamic linear regression was proposed.Firstly,the mapping model of feature map between the Scale-Invariant Feature Transform(SIFT)feature of image and the target true density map was established,and the feature map containing target and background features was obtained by using aforementioned mapping model and SIFT feature.Then,according to the facts of the less background changes in the monitoring video and the relatively stable background features in the feature map,the regression model of people counting was established by the first-order dynamic linear regression from the integration of feature map and the actual number of people.Finally,the estimated number of people was obtained through the regression model.The experiments were performed on the datasets of MALL and PETS2009.The experimental results show that,compared with the cumulative attribute space method,the mean absolute error of the proposed method is reduced by2.2%,while compared with the first-order dynamic linear regression method based on corner detection,the mean absolute error and the mean relative error of the proposed method are respectively reduced by6.5%and2.3%.
作者 易国宪 熊淑华 何小海 吴晓红 郑新波 YI Guoxian;XIONG Shuhua;HE Xiaohai;WU Xiaohong;ZHENG Xinbo(College of Electronics and Information Engineering, Sichuan University, Chengdu Sichuan 610065, China;Dongguan Institute of Advanced Technology, Guangdong Dongguan 523000, China)
出处 《计算机应用》 CSCD 北大核心 2018年第12期3591-3595,共5页 journal of Computer Applications
基金 国家自然科学基金资助项目(11176018) 成都市产业集群协同创新项目(2016-XT00-00015-GX) 东莞市社会科技发展项目(2017507102428)~~
关键词 纹理 密度图 特征图谱 岭回归 动态线性回归 人数统计 texture density map feature map ridge regression dynamic linear regression people counting
  • 相关文献

参考文献3

二级参考文献15

  • 1万缨,韩毅,卢汉清.运动目标检测算法的探讨[J].计算机仿真,2006,23(10):221-226. 被引量:121
  • 2胡学敏.基于视频图像的密集人群智能监控关键技术的研究[D].武汉:武汉大学,2012. 被引量:1
  • 3Chow W T S, Cho S Y. Industrial Neural Vision System for Under- ground Railway Station Platform Surveillance[ J]. Advanced Engi- neering Informatics. 2002,16( 1 ) :73-83. 被引量:1
  • 4Huang C, Ai H Z, LI Yuan, et al. High-Performance Rotation In- variant Multiview Face Detection [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2007,29 ( 9 ) : 1112- 1123. 被引量:1
  • 5Anthony C Davies, Yin J H, Velastin S A. Crowd Monitoring Using Image Processing[ J]. Electronic and Communications Engineering Journal, 1995,7( 1 ) :37-47. 被引量:1
  • 6Fruin J J. Crowd Dynamics and the Design and Management of Public Place [ C ]//J Pauls (Ed.) , Int. Conf. on Building Use and Safety Technology. National Institute of Building Scenes, Washington DC, 1985 : 110-11. 被引量:1
  • 7Rahmalan H,Nixon M S,Carter J N. On Crowd Density Estimation for Surveillance [ J ]. The Institution of Engineering and Technology Conference on Crime and Security ,2006:540-545. 被引量:1
  • 8吕济民,曾昭贤,张茂军.基于非最大抑制聚类的视频人数估测方法[J].模式识别与人工智能,2012,25(1):150-156. 被引量:7
  • 9李雪峰,李晓华,周激流.基于完全局部二值模式的人群密度估计[J].计算机工程与设计,2012,33(3):1027-1031. 被引量:3
  • 10姚雪琴,李晓华,周激流.基于边缘对称性和HOG的行人检测方法[J].计算机工程,2012,38(5):179-182. 被引量:22

共引文献28

同被引文献15

引证文献2

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部