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个人信息Personal Information
教授
博士生导师
硕士生导师
任职 : 电子政务模拟仿真国家地方联合工程研究中心主任
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:信息与决策技术研究所
电子邮箱:yzwang@dlut.edu.cn
People counting with block histogram features and network flow constraints
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论文类型:会议论文
发表时间:2017-01-01
收录刊物:Scopus
页面范围:515-520
摘要:Recently, a directed graph model was presented to crowd counting in videos, and people flow was viewed as an integer flow on the constructed graph. The authors show that the network flow constraints on the graphs help to obtain consistent counting results. In this paper, we improve their work from two aspects. First, we design block histogram features for each group of people. Second, we simplify their directed graphs to contracted graphs by contracting all cut arcs. Since the network flow constraints on original graphs are equivalence to that on contracted ones, we propose a quadratic programming method with network flow constraints on contracted graphs to refine the crowd counting results. At last, experiments show that our block histogram features can deal better with perspective distortion problems and our approach obtains outstanding performance on PETS 2009 dataset. ? 2016 IEEE.