[1] [1] ZHANG Y X, DU B, ZHANG L P. A sparse representation-based binary hypothesis model for target detection in hyperspectral images ［J］. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(3): 1346-1354.

[2] [2] VAZQUEZ D, LOPEZ A M, MARIN J, et al.. Virtual and real world adaption for pedestrian detection ［J］.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(4): 797-809.

[3] [3] HUANG Y, FAN C E, ZHU Q P, et al.. HOG-LBP pedestrian detection ［J］.Opt. Precision Eng., 2013, 21(4): 1047-1053.(in Chinese)

[4] [4] PEDERSOLI M, GONZALEZ J, HU X, et al.. Toward real-time pedestrian detection based on a deformable template model ［J］. IEEE Transactions on Intelligence Transportation Systems, 2014, 15(1): 355-364.

[5] [5] LAMPERT C H, BLASCHKO M B, HOFMANN T. Efficient subwindow search: a branch and bound framework for object localization ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(12): 2129-2142.

[6] [6] YANG B, LEI Y Q. Vehicle detection and classification for low-speed congested traffic with anisotropic magnetoresistive sensor ［J］. IEEE Sensors Journal, 2015, 15(2): 1132-1138.

[7] [7] PEDERSOLI M, GONZALEZ J, BAGDANOV A D, et al.. Recursive coarse-to-fine localization for fast object detection ［C］. Proceedings of 11th European Conference on Computer Vision, 2010: 280-293.

[8] [8] GUALDI G, PRATI A, CUCCHIARA R. Multistage particle windows for fast and accurate object detection ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(6): 1589-1604.

[9] [9] YANG Y, LI SH P. Fast object detection with deformable part models and segment locations hint ［J］. Acta Automatic Sinca, 2012, 38(4): 540-548.(in Chinese)

[10] [10] MUNDER S, GAVRILA D. An experimental study on pedestrian classification ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(11): 1863-1868.

[11] [11] ENZWEILER M, GAVRILA D. Monocular pedestrian detection: survey and experiments ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(12): 2179-2195.

[12] [12] SUN R, CHEN J, GAO J. Fast pedestrian detection based on saliency detection and HOG-NMF features ［J］.Journal of Electronics & Information Technology, 2013, 35(8): 1921-1926.(in Chinese)

[13] [13] SUN W, ZHAO C, SUN M. Learning based particle filtering object tracking for visible-light systems ［J］. International Journal for Light and Electron Optics, 2015, 126(19): 1830-1837.

[14] [14] YANG L P, GU X H. Relative gradient histogram features for face recognition ［J］.Opt. Precision Eng., 2014, 22(1): 152-159.(in Chinese)

[15] [15] QIAN SH, CHEN Z H, LIN M Q, et al.. Saliency detection based on conditional random field and image segmentation ［J］. ACTA AUTOMATIC SINCA, 2015, 41(4): 711-724.(in Chinese)

[16] [16] XIU CH B, WEI SH A. Camshift tracking with saliency histogram ［J］. Opt. Precision Eng., 2015, 23(6): 1749-1757.(in Chinese)

[17] [17] LI W Y, WANG P, QIAO H. A survey of visual attention based methods for object tracking ［J］.ACTA AUTOMATIC SINCA, 2014, 40(4): 561-576.

[18] [18] GUO C, ZHANG L. A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression ［J］. IEEE Transactions on Image Processing, 2010, 19(1): 185-198.

[19] [19] ACHANTA R, HEMAMI S, ESTRADA F, et al.. Frequency-tuned salient region detection ［C］. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Miami: FL, 2009: 1597-1604.

[20] [20] HOU X D, HAREL J, KOCH C, et al.. Image signature: highlighting sparse salient regions ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(1): 194-201.