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文件名称:A Neural-Based Crowd Estimation
文件大小:254KB
文件格式:PDF
更新时间:2013-02-12 07:04:59
Crowd Estimation
Abstract—A neural-based crowd estimation system for surveillance in
complex scenes at underground station platform is presented. Estimation
is carried out by extracting a set of significant features from sequences
of images. Those feature indexes are modeled by a neural network to
estimate the crowd density. The learning phase is based on our proposed
hybrid of the least-squares and global search algorithms which are
capable of providing the global search characteristic and fast convergence
speed. Promising experimental results are obtained in terms of accuracy
and real-time response capability to alert operators automatically.
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