Correlation Filter Tracking Algorithm for Adaptive Feature Selection

Wanjun Liu; Hu Sun; Wentao Jiang

doi:10.3788/AOS201939.0615004

[1] Zhang T Z, Xu C S, Yang M H. Multi-task correlation particle filter for robust object tracking. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 4819-4827(2017).

Zhang T Z, Xu C S, Yang M H. Multi-task correlation particle filter for robust object tracking. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 4819-4827(2017).

[2] Zhao G P, Shen Y P, Wang J Y. Adaptive feature fusion object tracking based on circulant structure with kernel[J]. Acta Optica Sinica, 37, 0815001(2017).

Zhao G P, Shen Y P, Wang J Y. Adaptive feature fusion object tracking based on circulant structure with kernel[J]. Acta Optica Sinica, 37, 0815001(2017).

[3] Zhang Z, Sun J, Yang L T. Tracking algorithm based on correlation filter fusing and keypoint matching[J]. Acta Optica Sinica, 39, 0215001(2019).

Zhang Z, Sun J, Yang L T. Tracking algorithm based on correlation filter fusing and keypoint matching[J]. Acta Optica Sinica, 39, 0215001(2019).

[4] Ge B Y, Zuo X Z, Hu Y J. Long-term object tracking based on feature fusion[J]. Acta Optica Sinica, 38, 1115002(2018).

Ge B Y, Zuo X Z, Hu Y J. Long-term object tracking based on feature fusion[J]. Acta Optica Sinica, 38, 1115002(2018).

[5] Lu H C, Li P X, Wang D. Visual object tracking: a survey[J]. Pattern Recognition and Artificial Intelligence, 31, 61-76(2018).

Lu H C, Li P X, Wang D. Visual object tracking: a survey[J]. Pattern Recognition and Artificial Intelligence, 31, 61-76(2018).

[6] Bolme D S, 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).

Bolme D S, 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).

[7] 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, et al. Computer Vision-ECCV 2012. Berlin, Heidelberg: Springer, 7575, 702-715(2012).

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, et al. Computer Vision-ECCV 2012. Berlin, Heidelberg: Springer, 7575, 702-715(2012).

[8] 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). http://doi.ieeecomputersociety.org/10.1109/TPAMI.2014.2345390

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). http://doi.ieeecomputersociety.org/10.1109/TPAMI.2014.2345390

[9] 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).

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).

[10] 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).

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).

[11] Tang M, Feng J Y. Multi-kernel correlation filter for visual tracking. [C]//2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 3038-3046(2015).

Tang M, Feng J Y. Multi-kernel correlation filter for visual tracking. [C]//2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 3038-3046(2015).

[12] Zhang K H, Zhang L, Yang M H et al. -11-08)[2018-12-15](2013). https://arxiv.org/pdf/1311.1939.pdf.

Zhang K H, Zhang L, Yang M H et al. -11-08)[2018-12-15](2013). https://arxiv.org/pdf/1311.1939.pdf.

[13] 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).

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).

[14] Possegger H, Mauthner T, Bischof H. In defense of color-based model-free tracking. [C]//2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 2113-2120(2015).

Possegger H, Mauthner T, Bischof H. In defense of color-based model-free tracking. [C]//2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 2113-2120(2015).

[15] Wang M M, Liu Y, Huang Z Y. Large margin object tracking with circulant feature maps. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 4800-4808(2017).

Wang M M, Liu Y, Huang Z Y. Large margin object tracking with circulant feature maps. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 4800-4808(2017).

[16] Bian J W, Lin W Y, Matsushita Y et al. GMS: grid-based motion statistics for fast, ultra-robust feature correspondence. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2828-2837(2017).

Bian J W, Lin W Y, Matsushita Y et al. GMS: grid-based motion statistics for fast, ultra-robust feature correspondence. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2828-2837(2017).

[17] Wu Y, Lim J, Yang M H. Online object tracking: a benchmark. [C]//2013 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2013, Portland, OR, USA. New York: IEEE, 2411-2418(2013).

Wu Y, Lim J, Yang M H. Online object tracking: a benchmark. [C]//2013 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2013, Portland, OR, USA. New York: IEEE, 2411-2418(2013).

[18] Wu Y, Lim J, Yang M H. Object tracking benchmark[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 1834-1848(2015).

Wu Y, Lim J, Yang M H. Object tracking benchmark[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 1834-1848(2015).

[19] Li Y, Zhu J K. A scale adaptive kernel correlation filter tracker with feature integration[M]. //Agapito L, Bronstein M, Rother C. Computer Vision-ECCV 2014 Workshops. Cham: Springer, 8693, 254-265(2015).

Li Y, Zhu J K. A scale adaptive kernel correlation filter tracker with feature integration[M]. //Agapito L, Bronstein M, Rother C. Computer Vision-ECCV 2014 Workshops. Cham: Springer, 8693, 254-265(2015).

[20] 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).

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).

[21] Galoogahi H K, Fagg A, Lucey S. Learning background-aware correlation filters for visual tracking. [C]//2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 1144-1152(2017).

Galoogahi H K, Fagg A, Lucey S. Learning background-aware correlation filters for visual tracking. [C]//2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 1144-1152(2017).

[22] Li F, Tian C, Zuo W M et al. Learning spatial-temporal regularized correlation filters for visual tracking. [C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 4904-4913(2018).

Li F, Tian C, Zuo W M et al. Learning spatial-temporal regularized correlation filters for visual tracking. [C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 4904-4913(2018).

[23] Danelljan M, Bhat G, Khan F S et al. ECO: efficient convolution operators for tracking. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 6931-6939(2017).

Danelljan M, Bhat G, Khan F S et al. ECO: efficient convolution operators for tracking. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 6931-6939(2017).