Crowd counting in public video surveillance by label distribution learning

Author:

Zhang Zhaoxiang,Wang MoORCID,Geng Xin

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Program for New Century Excellent Talents in University

Beijing Higher Education Young Elite Teacher Project

Fundamental Research Funds for the Central Universities, and the Key Lab of Computer Network and Information Integration of Ministry of Education of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference41 articles.

1. Chen Change Loy, Ke Chen, Shaogang Gong, Tao Xiang, Crowd counting and profiling: methodology and evaluation, in: Modeling, Simulation and Visual Analysis of Crowds, Springer, 2013, pp. 347–382.

2. Antoni B. Chan, Z.-S.J. Liang, Nuno Vasconcelos, Privacy preserving crowd monitoring: counting people without people models or tracking, in: IEEE Conference on Computer Vision and Pattern Recognition, 2008, CVPR 2008, IEEE, 2008, pp. 1–7.

3. Navneet Dalal, Bill Triggs, Histograms of oriented gradients for human detection, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, CVPR 2005, vol. 1, IEEE, 2005, pp. 886–893.

4. Object detection with discriminatively trained part-based models;Felzenszwalb;IEEE Trans. Pattern Anal. Mach. Intell.,2010

5. Segmentation and tracking of multiple humans in crowded environments;Zhao;IEEE Trans. Pattern Anal. Mach. Intell.,2008

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