[1] [1] S Avidan. Support vector tracking [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(8): 1064-1072.

[2] [2] O Chapelle, B Scholkopf, A Zien. Semi-Supervised Learning [M]. London: The MIT Press, 2006.

[3] [3] H Grabner, H Bischof. On-line boosting and vision [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2006, 1: 260-267

[4] [4] A Saffari, C Leistner, J Santner, et al.. On-line random forests [C]. IEEE International Conference on Computer Vision Workshop, 2009: 1393-1400.

[5] [5] M Godec, C Leistner, A Saffari, et al.. On- line random naive bayes for tracking [C]. IEEE International Conference on Pattern Recognition, 2010: 3545-3548.

[6] [6] S Hare, A Saffari, P H Torr. Struck: Structured output tracking with kernels [C]. IEEE International Conference on Computer Vision, 2011: 263-270.

[7] [7] A Bosch, A Zisserman, X Muoz. Image classification using random forests and ferns [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2007: 1-8.

[8] [8] M Heikkila, M Pietikainen. A texture- based method for modeling the background and detecting moving objects [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(4): 657-662.

[9] [9] M Calonder, V Lepetit, C Strecha, et al.. Brief: Binary robust independent elementary features [C]. European Conference on Computer Vision, 2010: 778-792.

[10] [10] S Belongie, J Malik, J Puzicha. Shape matching and object recognition using shape contexts [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(4): 509-522.

[11] [11] B Wu, R Nevatia. Detection and tracking of multiple, partially occluded humans by bayesian combination of edgelet based part detectors [J]. International Journal of Computer Vision, 2007, 75(2): 247-266.

[12] [12] N Dalal, B Triggs. Histograms of oriented gradients for human detection [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2005, 1: 886-893.

[13] [13] A Bosch, A Zisserman, X Munoz. Representing shape with a spatial pyramid kernel [C]. ACM International Conference on Image and Video Retrieval, 2007: 401-408.

[14] [14] S Avidan. Ensemble tracking [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(2): 261-271.

[15] [15] D A Ross, J Lim, R S Lin, et al.. Incremental learning for robust visual tracking [J]. International Journal of Computer Vision, 2008, 77(1): 125-141.

[16] [16] S Gu, Y Zheng, C Tomasi. Efficient visual object tracking with online nearest neighbor classifier [C]. Asian Conference on Computer Vision, 2010: 271-282.

[17] [17] P Viola, M Jones. Rapid object detection using a boosted cascade of simple features [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2001, 1: I-511-I-518.

[18] [18] C H Lampert, M B Blaschko, T Hofmann. Efficient subwindow search: a branch and bound framewrok for object localization [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 31(12): 2129-2142.

[19] [19] B Leibe, A Leonardis, B Schiele. Robust object detection with interleaved categorization and segmentation [J]. International Journal of Computer Vision, 2008, 77(1-3): 259-289.

[20] [20] P F Felzenszwalb, D P Huttenlocher. Pictorial structures for object recognition [J]. International Journal of Computer Vision, 2005, 61(1): 55-79.

[21] [21] A Opelt, A Pinz, A Zisserman. Learning an alphabet of shape and appearance for multi-class object detection [J]. International Journal of Computer Vision, 2008, 80(1): 16-44.

[22] [22] Zhang Hui, Zhao Baojun, Tang Linbo, et al.. Infrared object tracking based on adaptive multi-features integration [J]. Acta Optica Sinica, 2010, 30(5): 1291-1296.

[23] [23] Anping Li, Zhongliang Jiang, Shiqiang Hu. Particle filter based visual tracking with multi-cue adaptvie fusion [J]. Chin Opt Lett, 2005, 3(6): 326-329.

[24] [24] Z Kalal, K Mikolajczyk, J Matas. Tracking-learning-detection [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 34(7): 1409-1422.

[25] [25] Y Wu, M H Yang, J Lim. Online object tracking: A benchmark [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 2411-2418.