Improved Algorithm to Count Dense Crowds
Handles higher crowd densities Requires only still images
Crowd management Event attendance News reporting
The new method from UCF to count dense crowds of people works by analyzing an image at multiple densities. Although the density of people varies across the image, adjacent patches should be similar allowing for an accurate estimate by counting individuals in small patches. In medium density crowds, the process recognizes the periodic occurrence of heads ΓÇô the harmonics, which it captures through Fourier analysis, and, in high density crowds, the texture of the crowd is captured through scale-invariant feature transform. The algorithm functions with new constraints in multi-scale Markov random field to infer a single count over the entire image.
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