1. Jin, Z. and Bhanu, B., "Single camera mult i-person tracking based
on crowd simulat ion", in Proceedings of t he 21st International
Conference on Pat tern Recognit ion (ICPR2012), IEEE. V,
(2012), 3660-3663.
2. Andriyenko, A., Rot h, S. and Schindler, K., "An analytical
formulat ion of global occlusion reasoning for mult i-target
t racking", in 2011 IEEE International Conference on Computer
Vision Workshops (ICCV Workshops), IEEE., (2011), 18391846.
3. Wu, Z., Thangali, A., Sclaroff, S. and Bet ke, M., "Coupling
det ect ion and dat a associat ion for mult iple object t racking", in
2012 IEEE Conference on Comput er Vision and Pattern
Recognit ion, IEEE., (2012), 1948-1955.
4. de Pádua, P.H., Pádua, F.L., Sousa, M.T. and Pereira, M.d.A.,
"Part icle filter-based predictive tracking of futsal players from a single st at ionary camera", in 2015 28th SIBGRAPI Conference
on Graphics, Pat t erns and Images, IEEE., (2015), 134-141.
5. García, F., Prioletti, A., Cerri, P. and Broggi, A., "Phd filter for
vehicle t racking based on a monocular camera", Expert Systems
with Applications, Vol. 91, (2018), 472-479.
6. Zulkifley, M.A., "Robust single object tracker based on kernelled
pat ch of a fixed rgb camera", Optik-International Journal for
Light and Electron Optics, Vol. 127, No. 3, (2016), 1100-1110.
7. Liem, M.C. and Gavrila, D.M., "Joint multi-person det ection and
t racking from overlapping cameras", Computer Vision and
Image Understanding, Vol. 128, (2014), 36-50.
8. Chen, X., Qin, Z., An, L. and Bhanu, B., "An online learned
element ary grouping model for mult i-t arget t racking", in
Proceedings of t he IEEE Conference on Computer Vision and
Pat t ern Recognit ion., (2014), 1242-1249.
9. Lee, Y.-G., Tang, Z. and Hwang, J.-N., "Online-learning-based
human t racking across non-overlapping cameras", IEEE
Transactions on Circuits and Systems for Video Technology,
Vol. 28, No. 10, (2017), 2870-2883.
10. Yoon, K., Song, Y.-m. and Jeon, M., "Mult iple hypothesis
t racking algorithm for mult i-target mult i-camera t racking with
disjoint views", IET Image Processing, Vol. 12, No. 7, (2018),
1175-1184.
11. Lin, D.-T. and Huang, K.-Y., "Collaborative pedestrian tracking
and dat a fusion wit h multiple cameras", IEEE Transactions on
Information Forensics and Security, Vol. 6, No. 4, (2011),
1432-1444.
12. Tesfaye, Y.T., Zemene, E., Prati, A., Pelillo, M. and Shah, M.,
"Mult i-t arget tracking in multiple non-overlapping cameras using
const rained dominant set s", arXiv preprint arXiv:1706.06196,
(2017), 1-15.
13. Wang, N. and Yeung, D.-Y., "Learning a deep compact image
representation for visual t racking", in Advances in neural
informat ion processing syst ems., (2013), 809-817.
14. Chen, Y., Yang, X., Zhong, B., Pan, S., Chen, D. and Zhang, H.,
"Cnnt racker: Online discriminat ive object t racking via deep
convolutional neural net work", Applied Soft Computing, Vol.
38, (2016), 1088-1098.
15. Hong, S., You, T., Kwak, S. and Han, B., "Online t racking by
learning discriminative saliency map wit h convolutional neural
net work", in Int ernational conference on machine learning.,
(2015), 597-606.
16. Zhang, P., Zhuo, T., Huang, W., Chen, K. and Kankanhalli, M.,
"Online object t racking based on cnn wit h spat ial-temporal
saliency guided sampling", Neurocomputing, Vol. 257, (2017),
115-127.
17. Wang, H., Zhang, S., Ge, H., Chen, G. and Du, Y., "Robust visual
t racking via semiadapt ive weight ed convolutional feat ures",
IEEE Signal Processing Letters, Vol. 25, No. 5, (2018), 670-
674.
18. Qian, X., Han, L., Wang, Y. and Ding, M., "Deep learning
assist ed robust visual t racking wit h adapt ive particle filtering",
Signal Processing: Image Communication, Vol. 60, (2018),
183-192.
19. Sun, R., Wang, X. and Yan, X., "Robust visual t racking based on
ext reme learning machine wit h multiple kernels features fusion",
in 2017 3rd IEEE Int ernational Conference on Computer and
Communicat ions (ICCC), IEEE., (2017), 2029-2033.
20. Hao, Z., Liu, G. and Zhang, H., "Correlation filter-based visual
t racking via adaptive weighted cnn features fusion", IET Image
Processing, Vol. 12, No. 8, (2018), 1423-1431.
21. Simonyan, K. and Zisserman, A., "Very deep convolutional
net works for large-scale image recognit ion", arXiv preprint
arXiv:1409.1556, (2014).
)
