[1] Zuo W M, Wu X H, Lin L et al. Learning support correlation filters for visual tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41, 1158-1172(2019).
[2] Zhu G, Porikli F, Li H D. Beyond local search: tracking objects everywhere with instance-specific proposals. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 943-951(2016).
[3] Zhu G B, Wang J Q, Wu Y et al. Collaborative correlation tracking[C]∥British Machine Vision Conference 2015, September 7-10, 2015, Swansea, Wales, UK. Durham, England,, 184-184(2015).
[8] Vojir T, Noskova J, Matas J. Robust scale-adaptive mean-shift for tracking[J]. Pattern Recognition Letters, 49, 250-258(2014).
[9] Bolme D, Beveridge J R, Draper B A et al. Visual object tracking using adaptive correlation filters. [C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 2544-2550(2010).
[10] Henriques J F, Caseiro R, Martins P et al. Exploiting the circulant structure of tracking-by-detection with kernels[M]. ∥Fitzgibbon A, Lazebnik S, Perona P,
[11] Danelljan M, Khan F S, Felsberg M et al. Adaptive color attributes for real-time visual tracking. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition CVPR, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 1090-1097(2014).
[12] Henriques J F, Caseiro R, Martins P et al. High-speed tracking with kernelized correlation filters[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 583-596(2015).
[13] Danelljan M, Häger G, Khan F et al. Accurate scale estimation for robust visual tracking [C]∥British Machine Vision Conference 2014, September 1-5, 2014, Nottingham. Durham, England,, 65(2014).
[14] Danelljan M, Häger G, Khan F S et al. Discriminative scale space tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1561-1575(2017).
[15] Li Y, Zhu J K. A scale adaptive kernel correlation filter tracker with feature integration[M]. ∥Agapito L, Bronstein M, Rother C,
[16] Danelljan M, Häger G, Khan F S et al. Learning spatially regularized correlation filters for visual tracking. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 4310-4318(2015).
[17] Bertinetto L, Valmadre J, Golodetz S et al. Staple: complementary learners for real-time tracking. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 1401-1409(2016).
[18] Wu Y, Lim J, Yang M-H. Online object tracking: a benchmark. [C]∥2013 IEEE Conference on Computer Vision and Pattern Recognition CVPR, June 23-28, 2013, Portland, OR, USA. New York: IEEE, 2411-2418(2013).
[19] Wu Y, Lim J, Yang M H. Object tracking benchmark[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 1834-1848(2015).
[20] Scholkopf B, Smola A J[M]. Learning with kernels, 645(2005).