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 language | English |
|---|---|
| Title of host publication | Advances in swarm intelligence: Third international conference, ICSI 2012, Shenzhen, China, June 17-20, 2012 proceedings, part II |
| Editors | Ying TAN, Yuhui SHI, Zhen JI |
| Place of Publication | Berlin, Heidelberg |
| Publisher | Springer |
| Pages | 228-235 |
| ISBN (Electronic) | 9783642310201 |
| ISBN (Print) | 9783642310195 |
| DOIs | |
| Publication status | Published - 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