[1] 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.

[2] Walther D, Koch C. Modeling attention to salient proto-objects[J]. Neural Networks, 2006, 19(9): 1395-1407.

[3] Liu T, Yuan Z J, Sun J, et al. Learning to detect a salient object[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(2): 353-367.

[4] Hou X D, Zhang L Q. Saliency detection:a spectral residual approach[C]//IEEE Conference on Computer Vision and Pattern Recognition, 2007:1-8.

[5] Guo C L, Ma Q, Zhang L M, et al. Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform[C]//IEEE Conference on Computer Vision and Pattern Recognition, 2008: 1-8.

[6] Wolf W. Key frame selection by motion analysis[C]//IEEE International Conference on Acoustics, Speech and Signal Processing, 1996: 1228-1231.

[7] Li K M, Zhang T, Hu X T, et al. Human-centered attention models for video summarization[C]//ACM Special Interest Group on Computer-Human Interaction, 2010: 1-27.

[8] Ma Y F, Hua X S, Lu L, et al. A generic framework of user attention model and its application in video summarization[J]. IEEE Transactions on Multimedia, 2005, 7(5): 907-919.

[9] Wang R X, McKenna S, Han J W, et al. Visualizing image collections using high-entropy layout distributions[J]. IEEE Transactions on Multimedia, 2010, 12(8): 803-813.

[10] Pierre B, Itti L. Of bits and wows:a Bayesian theory of surprise with applications to attention[J]. Neural Networks, 2010, 23(5):649-666.

[11] Mei T, Hua X S, Yang L J, et al. Videosense: towards effective online video advertising[C]//Proceedings of the 15th International Conference on Multimedia, 2007: 1075-1084.