2 May 2012 Crowd density estimation based on statistical analysis of local intra-crowd motions for public area surveillance
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Abstract
Crowd density estimation in public areas with people gathering and waiting has been a challenging problem for visual surveillance over many years. Tiny motions, like when people turn around, wander about, and turn their heads, happen randomly now and then in crowds, which makes it difficult to achieve high-performance crowd density estimation based on traditional foreground detection. A novel accumulated mosaic image difference feature is proposed to represent these complicated random motion patterns for accurate foreground detection. The obtained foreground is then normalized based on the perspective distortion correction model to achieve a reasonable crowd density measurement for observed areas. Numerous experiments are conducted in different scenes of various view angles, and experimental results demonstrate the effectiveness and robustness of our proposed method.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Zhaoxiang Zhang, Zhaoxiang Zhang, Min Li, Min Li, } "Crowd density estimation based on statistical analysis of local intra-crowd motions for public area surveillance," Optical Engineering 51(4), 047204 (2 May 2012). https://doi.org/10.1117/1.OE.51.4.047204 . Submission:
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