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  • 标题:Large Crowd Count Based on Improved SURF Algorithm
  • 本地全文:下载
  • 作者:Haining Zhang ; Huanbo Gao
  • 期刊名称:TELKOMNIKA (Telecommunication Computing Electronics and Control)
  • 印刷版ISSN:2302-9293
  • 出版年度:2014
  • 卷号:12
  • 期号:4
  • 页码:865-874
  • DOI:10.12928/telkomnika.v12i4.362
  • 语种:English
  • 出版社:Universitas Ahmad Dahlan
  • 摘要:This paper uses an analysis of Speeded up Robust Feature (SURF), based on the method of Linear Interpolation for camera distortion calibration, for high-density crowd counting. The eigenvalues are built on the Gray Level Co-occurrence Matrix (GLCM) features and the SURF features. Though the method of linear interpolation, weight values are interpolated to reduce the error, which is caused by camera distortion calibration. The optimized crowd’s feature vector can be got then. Through the method of support vector regression, the crowd’s number can be forecast by training model. The experiment result shows that the method of this paper has a higher accuracy than the previous methods.
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