A neural-based crowd estimation by hybrid global learning algorithm

Siu Yeung Cho, Tommy W.S. Chow, Chi Tat Leung

Research output: Journal PublicationArticlepeer-review

154 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)535-541
Number of pages7
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number4
Publication statusPublished - Aug 1999
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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