Video-base people counting and gender recognition

Yuen Sum WONG, Cho Wing TAM, Siu Mo LEE, Chuen Pan CHAN, Hong FU

Research output: Chapter in Book/Report/Conference proceedingChapters

6 Citations (Scopus)

Abstract

Video based people counting and gender recognition are important but challenging tasks. A neural network method for video-base people counting and gender recognition is proposed in this paper. A multilayer perceptron structure is constructed and meaningful features from target video are extracted as input. The neural network is trained by back-propagation training algorithm. This method is experimented on four videos, including more than 240 peoples. Experiment results have shown the effectiveness of this method. Copyright © 2012 Springer-Verlag Berlin Heidelberg.
Original languageEnglish
Title of host publicationAdvances in swarm intelligence: Third international conference, ICSI 2012, Shenzhen, China, June 17-20, 2012 proceedings, part II
EditorsYing TAN, Yuhui SHI, Zhen JI
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages228-235
ISBN (Electronic)9783642310201
ISBN (Print)9783642310195
DOIs
Publication statusPublished - 2012

Citation

Wong, Y. S., Tam, C. W., Lee, S. M., Chan, C. P., & Fu, H. (2012). Video-base people counting and gender recognition. In Y. Tan, Y. Shi, & Z. Ji (Eds.), Advances in swarm intelligence: Third international conference, ICSI 2012, Shenzhen, China, June 17-20, 2012 proceedings, part II (pp. 228-235). Berlin, Heidelberg: Springer.

Keywords

  • People counting
  • Gender recognition
  • Video understanding

Fingerprint

Dive into the research topics of 'Video-base people counting and gender recognition'. Together they form a unique fingerprint.