References
- B. Leibe, E. Seemann, and B. Schiele, "Pedestrian detection in crowded scenes," IEEE Conference on Computer Vision and Pattern Recognition, pp. 878-885, June 2005.
- J. Lim and W. Kim, "Detecting and tracking of multiple pedestrians using motion, color information and the AdaBoost algorithm," Multimedia Tools and Applications, vol. 65, no. 1, pp. 161-179, June 2012.
- G. Brostow and R. Cipolla, "Unsupervised bayesian detection of independent motion in crowds," Proc. International Conference on Computer Vision and Pattern Recognition, pp. 594-601, June 2006.
- V. Rabaud and S. Belongie, "Counting crowded moving objects," Proc. International Conference on Computer Vision and Pattern Recognition, pp. 705-711, June 2006.
- C. Zhang, H. Li, X. Wang, and X. Yang, "Cross-scene crowd counting via deep convolutional neural networks," IEEE Conf. Computer Vision and Pattern Recognition, 2015.
- H. Fradi and J. Dugelay, "People counting system in crowded scenes based on feature regression," in Proc. European Signal Processing Conference, Aug. 2012.
- A. Chan, Z. Liang, and N. Vasconcelos, "Privacy preserving crowd monitoring: counting people without people models or tracking," Proc. International Conference on Computer Vision and Pattern Recognition, June 2008.
- K. Kim and Y. Yoon, "Pedestrian counting system based on average filter tracking for measuring advertisement effectiveness of digital signage," Journal of Broadcast Engineering, Vol. 21, No. 4, July 2016.
- A. Albiol, M. J. Silla, A. Albiol, and J. M. Mossi, "Video analysis using corner motion statistics," Proc. IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, 2009.
- C. Y. Jeong, S. Choi, and S. W. Han, "A method for counting moving and stationary people by interest point classification," Proc. IEEE International Conference on Image Processing, Melbourne, Sep. 2013.
- Z. Zivkovic, and F. van der Heijden, "Efficient adaptive density estimation per image pixel for the task of background subtraction," Pattern Recognition Letters, vol. 27, no. 7, pp. 773-780, May 2006. https://doi.org/10.1016/j.patrec.2005.11.005
- N. A. Cressie, Statistics for spatial data (revised edition), John Wiley & Sons, 1993.
- S. Bahroun, Z. Belhadj, and N. Boujemaa, "Semantic region labelling using a point pattern analysis," Proc. European Signal Processing Conference, Lausanne, Aug. 2008.
- D. Conte, P. Foggia, G. Percannella, F. Tufano, and M. Vento, "Counting moving people in videos by salient points detection," Proc. International Conference on Pattern Recognition, Istanbul, Aug. 2010.
- T. Zhao and R. Nevatia, "Bayesian human segmentation in crowded situations," Proc. International Conference on Computer Vision and Pattern Recognition, vol. 2, June 2003.
- PETS: performance evaluation of tracking and surveillance workshop at CVPR 2009. Miami, Florida (2009) http://www.cvg.reading.ac.uk/PETS2009/a.html.
- T. Ojala, M. Pietikainen, and T. Maenpaa, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 971-987, July 2002. https://doi.org/10.1109/TPAMI.2002.1017623
- M. Heikkila and M. Pietikainen, "A texture-based method for modeling the background and detecting moving objects," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 4, pp. 657-662, Apr. 2006. https://doi.org/10.1109/TPAMI.2006.68