Multi-source Multi-scale Counting in Extremely Dense Crowd Images

  title={Multi-source Multi-scale Counting in Extremely Dense Crowd Images},
  author={Haroon Idrees and Imran Saleemi and Cody Seibert and Mubarak Shah},
  journal={2013 IEEE Conference on Computer Vision and Pattern Recognition},
We propose to leverage multiple sources of information to compute an estimate of the number of individuals present in an extremely dense crowd visible in a single image. Due to problems including perspective, occlusion, clutter, and few pixels per person, counting by human detection in such images is almost impossible. Instead, our approach relies on multiple sources such as low confidence head detections, repetition of texture elements (using SIFT), and frequency-domain analysis to estimate… CONTINUE READING
Highly Influential
This paper has highly influenced 45 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 210 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 128 extracted citations

211 Citations

Citations per Year
Semantic Scholar estimates that this publication has 211 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 26 references

: Dataset and challenge

  • W. Ge, R. Collins
  • 2010

How is crowd size estimated

  • R. Melina
  • In Life’,
  • 2010
1 Excerpt

Similar Papers

Loading similar papers…