- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Recently Accepted Articles ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Discrete Dynamics in Nature and Society
Volume 2014 (2014), Article ID 712041, 11 pages
Pedestrian Detection and Tracking for Counting Applications in Metro Station
Beijing University of Technology, Chaoyang Distract Beijing, China
Received 9 November 2013; Revised 12 January 2014; Accepted 19 January 2014; Published 27 February 2014
Academic Editor: Wuhong Wang
Copyright © 2014 Chen Yan-yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- A. Mittal, A. Jain, and G. K. Agarwal, “Audio-video based people counting and security framework for traffic crossings,” Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, vol. 49, no. 3, pp. 377–391, 2007.
- Y. Hou and G. K. H. Pang, “People counting and human detection in a challenging situation,” IEEE Transactions on Systems, Man, and Cybernetics A, vol. 41, no. 1, pp. 24–33, 2011.
- A. B. Chan and N. Vasconcelos, “Counting people with low-level features and Bayesian regression,” IEEE Transactions on Image Processing, vol. 21, no. 4, pp. 2160–2177, 2012.
- G. Xiong, J. Cheng, X. Wu, Y. Chen, Y. Ou, and Y. Xu, “An energy model approach to people counting for abnormal crowd behavior detection,” Neurocomputing, vol. 83, pp. 121–135, 2012.
- C. Sacchi, G. Gera, L. Marcenaro, and C. S. Regazzoni, “Advanced image-processing tools for counting people in tourist site-monitoring applications,” Signal Processing, vol. 81, no. 5, pp. 1017–1040, 2001.
- A. J. Schofield, T. J. Stonham, and P. A. Mehta, “Automated people counting to aid lift control,” Automation in Construction, vol. 6, no. 5-6, pp. 437–445, 1997.
- K. Hashimoto, C. Kawaguchi, S. Matsueda, K. Morinaka, and N. Yoshiike, “People-counting system using multisensing application,” Sensors and Actuators A, vol. 66, no. 1–3, pp. 50–55, 1998.
- I. J. Amin, A. J. Taylor, F. Junejo, A. Al-Habaibeh, and R. M. Parkin, “Automated people-counting by using low-resolution infrared and visual cameras,” Measurement, vol. 41, no. 6, pp. 589–599, 2008.
- D. Huang and T. W. S. Chow, “A people-counting system using a hybrid RBF neural network,” Neural Processing Letters, vol. 18, no. 2, pp. 97–113, 2003.
- A. J. Schofield, P. A. Mehta, and T. J. Stonham, “A system for counting people in video images using neural networks to identify the background scene,” Pattern Recognition, vol. 29, no. 8, pp. 1421–1428, 1996.
- K. Kopaczewski, M. Szczodrak, A. Czyzewski, and H. Krawczyk, “A method for counting people attending large public events,” Multimedia Tools and Applications, 2013.
- A. G. Vicente, I. B. Munoz, P. J. Molina, and J. L. L. Galilea, “Embedded vision modules for tracking and counting people,” IEEE Transactions on Instrumentation and Measurement, vol. 58, no. 9, pp. 3004–3011, 2009.
- D. Conte, P. Foggia, G. Percannella, F. Tufano, and M. Vento, “A method for counting moving people in video surveillance videos,” Eurasip Journal on Advances in Signal Processing, vol. 2010, Article ID 231240, 10 pages, 2010.
- M. Goncalo, P. Paulo, and N. Urbano, “Vision-based pdestrian dtection using Haar-like fatures,” in Actas do Encontro Cientifico Guimaraes, pp. 45–50, April 2006.
- A. A. Shaikh, D. K. Kumar, and J. Gubbi, “Automatic visual speech segmentation and recognition using directional motion history images and Zernike moments,” The Visual Computer, vol. 29, no. 10, pp. 969–982, 2013.
- T. Pallejà, A. Guillamet, M. Tresanchez et al., “Implementation of a robust absolute virtual head mouse combining face detection, template matching and optical flow algorithms,” Telecommunication Systems, vol. 52, no. 3, pp. 1479–1489, 2013.