[1] Borji A, Itti L. State-of-the-art in visual attention modeling[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(1): 185-207.

[2] Lee W F, Huang T H, Yeh S L, et al. Learning-based prediction of visual attention for video signals[J]. IEEE Transactions on Image Processing, 2011, 20(11): 3028-3038.

[3] Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259.

[4] Zhang QR, Xiao HM. Biologically motivated salient regions detection approach[C]. Second International Symposium on Intelligent Information Technology Application, 2008: 1100- 1104.

[5] Lin WS, Huang YW. Intention-oriented computational visual attention model for learning and seeking image content[C]. IEEE Conference on Industrial Electronics and Applications, 2009: 1250- 1255.

[6] IttiL, BaldiP. A principled approach to detecting surprising events in video[C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005: 631- 637.

[7] Guo C L, Zhang L M. 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.

[8] Li XH, Lu HC, Zhang LH, et al. Saliency detection via dense and sparse reconstruction[C]. IEEE International Conference on Computer Vision, 2013: 2976- 2983.

[9] Liu Z, Zhang X, Luo S H, et al. Superpixel-based spatiotemporal saliency detection[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2014, 24(9): 1522-1540.

[10] Wang W G, Shen J B, Shao L. Consistent video saliency using local gradient flow optimization and global refinement[J]. IEEE Transactions on Image Processing, 2015, 24(11): 4185-4196.

[11] SinghA, Henry CH, Pratt MA. Learning to predict video saliency using temporal superpixels[C]. International Conference on Pattern Recognition Applications and Methods, 2015: 201- 209.

[12] RahtuE, KannalaJ, SaloM, et al. Segmenting Salient Objects from Images and Videos[M] //Rahtu E, Kannala J, Salo M, et al. eds. Heidelberg: Springer Berlin Heidelberg, 2010: 366- 379.

[13] Fang YM, WangZ, Lin WS. Video saliency incorporating spatiotemporal cues and uncertainty weighting[C]. IEEE International Conference on Multimedia and Expo (ICME), 2013: 3910- 3921.

[14] 李庆武, 周亚琴, 马云鹏, 等. 基于双目视觉的显著性目标检测方法[J]. 光学学报, 2018, 38(3): 331-343.

    Li Q W, Zhou Y Q, Ma Y P, et al. Salient object detection method based on binocular vision[J]. Acta Optica Sinica, 2018, 38(3): 331-343.

[15] Brox T, Malik J. Large displacement optical flow: descriptor matching in variational motion estimation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(3): 500-513.

[16] Wei YC, WenF, Zhu WJ, et al. Geodesic saliency using background priors[M] //Wei Y C, Wen F, Zhu W J, et al. eds. Heidelberg: Springer Berlin Heidelberg, 2012: 29- 42.

[17] 杨鑫, 张雷雷, 梁艳梅. 基于L0平滑的超像素块最短测地距离的显著区域提取方法[J]. 光电子·激光, 2017, 28(6): 657-662.

    Yang X, Zhang L L, Liang Y M. Salient region detection based on super-pixels and shortest geodesic distance after L0 smoothing[J]. Journal of Optoelectronics·Laser, 2017, 28(6): 657-662.

[18] Tsai D, Flagg M, Nakazawa A, et al. Motion coherent tracking using multi-label MRF optimization[J]. International Journal of Computer Vision, 2012, 100(2): 190-202.

[19] Hou X D, Harel J, Koch C. Image signature: highlighting sparse salient regions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(1): 194-201.

[20] 李秋林, 何家峰. 基于三帧差法和交叉熵阈值法的车辆检测[J]. 计算机工程, 2011, 37(4): 172-174.

    Li Q L, He J F. Vehicles detection based on three-frame-difference method and cross-entropy threshold method[J]. Computer Engineering, 2011, 37(4): 172-174.

[21] Barnich O, van Droogenbroeck M. ViBe: A universal background subtraction algorithm for video sequences[J]. IEEE Transactions on Image Processing, 2011, 20(6): 1709-1724.

[22] 王兴宝, 刘纯平, 费兰英, 等. 局部时空域模型的核密度估计目标检测方法[J]. 中国图象图形学报, 2012, 17(7): 813-820.

    Wang X B, Liu C P, Fei L Y, et al. Foreground object detection method using kernel density estimation of a local spatio-temporal model[J]. Journal of Image and Graphics, 2012, 17(7): 813-820.

[23] SuoP, Wang YJ. An improved adaptive background modeling algorithm based on Gaussian Mixture Model[C]. 9th International Conference on Signal Processing, 2008: 1436- 1439.

[24] 张正华, 许晔, 苏权, 等. 基于背景差分和混合帧差的运动目标检测[J]. 无线电工程, 2012, 42(8): 14-17.

    Zhang Z H, Xu Y, Su Q, et al. Moving object detection based on background subtraction and hybrid frame differencing[J]. Radio Engineering, 2012, 42(8): 14-17.