Bolme, D. S., Beveridge, J. R., Draper, B. A. and Lui, Y. M. 2010. Visual object tracking using adaptive correlation filters. 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, pp. 2544–2550.
Czyz, J., Ristic, B. and Macq, B. 2007. A particle filter for joint detection and tracking of color objects. Image and Vision Computing 25(8): 1271–1281.
García-Fernández, A. F., Williams, J. L., Granström, K. and Svensson, L. 2018. Poisson multi-bernoulli mixture filter: direct derivation and implementation. IEEE Transactions on Aerospace and Electronic Systems 54 August, pp. 1883–1901.
Hare, S., Golodetz, S., Saffari, A., Vineet, V., Cheng, M.-M., Hicks, S. L. and Torr, P. H. 2016. Struck: structured output tracking with kernels. IEEE Transactions on Pattern Analysis and Machine Intelligence 38(10): 2096–2109.
Henriques, J. F., Caseiro, R., Martins, P. and Batista, J. 2015. High-speed tracking with kernelized correlation filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 37(3): 583–596.
Hoseinnezhad, R., Vo, B. N. and Vo, B. T. 2013. Visual tracking in background subtracted image sequences via multi-bernoulli filtering. IEEE Transactions on Signal Processing 61 January, pp. 392–397.
Hoseinnezhad, R., Vo, B.-N., Vo, B.-T. and Suter, D. 2012. Visual tracking of numerous targets via multibernoulli filtering of image data. Pattern Recognition 45(10): 3625–3635.
Jorquera, F., Hernández, S. and Vergara, D. 2017. Multi target tracking using determinantal point processes. in Mendoza, M. and Velastin, S. (Eds), Iberoamerican Congress on Pattern Recognition Springer International Publishing, Cham, pp. 323–330.
Jorquera, F., Hernández, S. and Vergara, D. 2019. Probability hypothesis density filter using determinantal point processes for multi object tracking. Computer Vision and Image Understanding 183: 33–41.
Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R., Zajc, L. Č., Vojír, T., Bhat, G., Lukežič, A., Eldesokey, A., Fernández, G., García-Martín, Á., Iglesias-Arias, Á., Alatan, A. A., González-García, A., Petrosino, A., Memarmoghadam, A., Vedaldi, A., Muhič, A., He, A., Smeulders, A., Perera, A. G., Li, B., Chen, B., Kim, C., Xu, C., Xiong, C., Tian, C., Luo, C., Sun, C., Hao, C., Kim, D., Mishra, D., Chen, D., Wang, D., Wee, D., Gavves, E., Gundogdu, E., Velasco-Salido, E., Khan, F. S., Yang, F., Zhao, F., Li, F., Battistone, F., De Ath, G., Subrahmanyam, G. R. K. S., Bastos, G., Ling, H., Galoogahi, H. K., Lee, H., Li, H., Zhao, H., Fan, H., Zhang, H., Possegger, H., Li, H., Lu, H., Zhi, H., Li, H., Lee, H., Chang, H. J., Drummond, I., Valmadre, J., Martin, J. S., Chahl, J., Choi, J. Y., Li, J., Wang, J., Qi, J., Sung, J., Johnander, J., Henriques, J., Choi, J., van de Weijer, J., Herranz, J. R., Martínez, J. M., Kittler, J., Zhuang, J., Gao, J., Grm, K., Zhang, L., Wang, L., Yang, L., Rout, L., Si, L., Bertinetto, L., Chu, L., Che, M., Maresca, M. E., Danelljan, M., Yang, M.-H., Abdelpakey, M., Shehata, M., Kang, M., Lee, N., Wang, N., Miksik, O., Moallem, P., Vicente-Moñivar, P., Senna, P., Li, P., Torr, P., Raju, P. M., Ruihe, Q., Wang, Q., Zhou, Q., Guo, Q., Martín-Nieto, R., Gorthi, R. K., Tao, R., Bowden, R., Everson, R., Wang, R., Yun, S., Choi, S., Vivas, S., Bai, S., Huang, S., Wu, S., Hadfield, S., Wang, S., Golodetz, S., Ming, T., Xu, T., Zhang, T., Fischer, T., Santopietro, V., Štruc, V., Wei, W., Zuo, W., Feng, W., Wu, W., Zou, W., Hu, W., Zhou, W., Zeng, W., Zhang, X., Wu, X., Wu, X.-J., Tian, X., Li, Y., Lu, Y., Law, Y. W., Wu, Y., Demiris, Y., Yang, Y., Jiao, Y., Li, Y., Zhang, Y., Sun, Y., Zhang, Z., Zhu, Z., Feng, Z.-H., Wang, Z. and He, Z. 2019. The sixth visual object tracking vot2018 challenge results. in Leal-Taixé, L. and Roth, S. (Eds), Computer Vision – ECCV 2018 Workshops Springer International Publishing, Cham, pp. 3–53.
Kulesza, A. and Taskar, B. 2011. Learning determinantal point processes. Proceedings of the Twenty-Seventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-11), AUAI Press, Corvallis, OR, pp. 419–427.
Lee, D., Cha, G., Yang, M.-H. and Oh, S. 2016. Individualness and determinantal point processes for pedestrian detection. in Leibe, B., Matas, J., Sebe, N. and Welling, M. (Eds), European Conference on Computer Vision Springer International Publishing, Cham, pp. 330–346.
Li, B., Yan, J., Wu, W., Zhu, Z. and Hu, X. 2018. High performance visual tracking with siamese region proposal network. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8971–8980.
Mahler, R. P. S. 2003. Multitarget bayes filtering via first-order multitarget moments. IEEE Transactions on Aerospace and Electronic Systems 39(4): 1152–1178.
Privault, N. and Teoh, T. 2019. Second order multi-object filtering with target interaction using determinantal point processes. Tech. Rep. arXiv:1906.06522 [math.PR], ArXiV, June.
Reuter, S., Wilking, B., Wiest, J., Munz, M. and Dietmayer, K. 2013. Real-time multi-object tracking using random finite sets. IEEE Transactions on Aerospace and Electronic Systems 49(4): 2666–2678.
Ristic, B., Vo, B. T., Vo, B. N. and Farina, A. 2013. A tutorial on bernoulli filters: Theory, implementation and applications. IEEE Transactions on Signal Processing 61 July, pp. 3406–3430.
Solis Montero, A., Lang, J. and Laganiere, R. 2015. Scalable kernel correlation filter with sparse feature integration. 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, December, pp. 587–594.
Vo, B.-N., Vo, B.-T., Pham, N.-T. and Suter, D. 2010. Joint detection and estimation of multiple objects from image observations. IEEE Transactions on Signal Processing 58(10): 5129–5141.
Wang, N., Shi, J., Yeung, D.-Y. and Jia, J. 2015. Understanding and diagnosing visual tracking systems. The IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, December, pp. 3101–3109, doi: 10.1109/ICCV.2015.355.