[1] [1] Su S Z, Li S Z, Chen S Y, et al. A survey on pedestrian detection[ J]. Acta Electronica Sinica, 2012, 40(4): 814–820.

[2] [2] Benenson R, Omran M, Hosang J, et al. Ten years of pedestrian detection, what have we learned [C]//Proceedings of- Computer Vision - ECCV 2014 Workshops, 2014: 613–627.

[3] [3] Dollar P, Wojek C, Schiele B, et al. Pedestrian detection: an evaluation of the state of the art[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(4): 743–761.

[4] [4] Ouyang W L, Wang X G. Joint deep learning for pedestrian detection[C]//Proceedings of IEEE International Conference on Computer Vision, 2013: 2056–2063.

[5] [5] Zeng X Y, Ouyang W L, Wang X G. Multi-stage contextual deep learning for pedestrian detection[C]//Proceedings of IEEE International Conference on Computer Vision, 2013: 121–128.

[6] [6] Luo P, Tian Y L, Wang X G, et al. Switchable deep network for pedestrian detection[C]//Proceedings of Conference on Computer Vision and Pattern Recognition, 2014: 899–906.

[7] [7] Zeng X Y, Ouyang W L, Wang M, et al. Deep learning of scene-specific classifier for pedestrian detection[C]//Fleet D, Pajdla T, Schiele B, et al. Computer Vision – ECCV 2014. Cham: Springer, 2014: 472–487.

[8] [8] Dalal N, Triggs B. Histograms of oriented gradients for human detection[C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005: 886–893.

[9] [9] Ojala T, Pietik inen M, Harwood I. A comparative study of texture measures with classification based on featured distributions[ J]. Pattern Recognition, 1996, 29(1): 51–59.

[10] [10] Tribak H, Moughyt S, Zaz Y, et al. Remote QR code recognition based on HOG and SVM classifiers[C]//Proceedings of International Conference on Informatics and Computing, 2017: 137–141.

[11] [11] Wang X Y, Han T X, Yan S C. An HOG-LBP human detector with partial occlusion handling[C]//Proceedings of IEEE 12th International Conference on Computer Vision, 2010: 32–39.

[12] [12] Fan G J, Li B, Mu W Q, et al. HOGG: Gabor and hog-based human detection[C]//Proceedings of 8th International Conference on Information Technology in Medicine and Education, 2016: 562–566.

[13] [13] Peng Z R, Zhao M R, Yang W M, et al. Improved multispectral aggregate channel for pedestrian detection[J]. Opto-Electronic Engineering, 2017, 44(9): 882–887.

[14] [14] Zhao L H, Liu F, Wang Y J. Face recognition based on LBP and genetic algorithm[C]//Proceedings of Chinese Control and Decision Conference, 2016: 1582–1587.

[15] [15] Liu Y C, Huang S S, Lu C H, et al. Thermal pedestrian detection using block LBP with multi-level classifier[C]//Proceedings of International Conference on Applied System Innovation, 2017: 602–605.

[16] [16] Guo Z H, Zhang L, Zhang D. A completed modeling of local binary pattern operator for texture classification[J]. IEEE Transactions on Image Processing, 2010, 19(6): 1657–1663.

[17] [17] Cheng W L, Wang X J, Wan Z J, et al. Research and implementation of target tracking algorithm in compression domain on miniaturized DSP platform[J]. Opto-Electronic Engineering, 2017, 44(10): 972–982.

[18] [18] Ji L P, Ren Y, Liu G S, et al. Training-based gradient lbp feature models for multiresolution texture classification[J]. IEEE Transactions on Cybernetics, 2017, pp(99): 1–14.

[19] [19] Zhao Y, Huang D S, Jia W. Completed local binary count for rotation invariant texture classification[J]. IEEE Transactions on Image Processing, 2012, 21(10): 4492–4497.

[20] [20] Maji S, Berg A C, Malik J. Classification using intersection kernel support vector machines is efficient[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2008: 1–8.

[21] [21] Wojek C, Schiele B. A performance evaluation of single and multi-feature people detection[C]//Proceedings of the 30th DAGM symposium on Pattern Recognition, 2008: 82–91.

[22] [22] Watanabe T, Ito S. Two co-occurrence histogram features using gradient orientations and local binary patterns for pedestrian detection[C]//Proceedings of 2nd IAPR Asian Conference on Pattern Recognition, 2013: 415–419.

[23] [23] Viola P, Jones M J. Robust real-time face detection[J]. International Journal of Computer Vision, 2004, 57(2): 137–154.