Abstract
This Chapter introduces several saliency-based applications in the fields of computer vision and multimedia analysis. We aim to demonstrate that by simulating the saliency mechanism in human vision system, computer can process visual information as human vision system does and the processing results can better meet human perception.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Avidan, S., Shamir, A.: Seam carving for content-aware image resizing. In: ACM SIGGRAPH. ACM, New York (2007), doi:10.1145/1275808.1276390
Chalmond, B., Francesconi, B., Herbin, S.: Using hidden scale for salient object detection. IEEE Transactions on Image Processing 15(9), 2644–2656 (2006), doi:10.1109/TIP.2006.877380
Chang, C.H., Hsieh, K.Y., Chung, M.C., Wu, J.L.: Visa: Virtual spotlighted advertising. In: Proceedings of the 16th ACM International Conference on Multimedia, MULTIMEDIA 2008, pp. 837–840. ACM, New York (2008), doi:10.1145/1459359.1459500
Elazary, L., Itti, L.: Interesting objects are visually salient. Journal of Vision 8(3), 3, 1–15 (2008), doi:10.1167/8.3.3
Fu, H., Chi, Z., Feng, D.: Attention-driven image interpretation with application to image retrieval. Pattern Recognition 39(9), 1604–1621 (2006), doi:10.1016/j.patcog.2005.12.015
Gao, W., Tian, Y., Huang, T., Yang, Q.: Vlogging: A survey of videoblogging technology on the web. ACM Computing Surveys 42(4), 15, 1–57 (2010), doi:10.1145/1749603.1749606
Guo, J., Mei, T., Liu, F., Hua, X.S.: Adon: An intelligent overlay video advertising system. In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009, pp. 628–629. ACM, New York (2009), doi:10.1145/1571941.1572049
Lekakos, G., Papakiriakopoulos, D., Chorianopoulos, K.: An integrated approach to interactive and personalized tv advertising. In: Proceedings of Workshop on Personalization in Future TV (2001)
Li, H., Edwards, S.M., Hyun Lee, J.: Measuring the intrusiveness of advertisements: Scale development and validation. Journal of Advertising 31(2), 37–47 (2002)
Li, M., Clark, J.: Selective attention in the learning of invariant representation of objects. In: Preceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) - Workshops, pp. 93–93 (2005), doi:10.1109/CVPR.2005.522
Li, S., Lee, M.C.: Efficient spatiotemporal-attention-driven shot matching. In: Proceedings of the 15th Annual ACM International Conference on Multimedia, MULTIMEDIA 2007, pp. 178–187. ACM, New York (2007), doi:10.1145/1291233.1291275
Li, Y., Wan, K.W., Yan, X., Xu, C.: Real time advertisement insertion in baseball video based on advertisement effect. In: Proceedings of the 13th Annual ACM International Conference on Multimedia, MULTIMEDIA 2005, pp. 343–346. ACM, New York (2005), doi:10.1145/1101149.1101221
Li, Y., Tian, Y., Yang, J., Duan, L.Y., Gao, W.: Video retargeting with multi-scale trajectory optimization. In: Proceedings of the International Conference on Multimedia Information Retrieval, MIR 2010, pp. 45–54. ACM, New York (2010), doi:10.1145/1743384.1743399
Li, Z., Qin, S., Itti, L.: Visual attention guided bit allocation in video compression. Image Vision Computing 29(1), 1–14 (2011), doi:10.1016/j.imavis.2010.07.001
López, M.T., Fernández-Caballero, A., Fernández, M.A., Mira, J., Delgado, A.E.: Visual surveillance by dynamic visual attention method. Pattern Recognition 39(11), 2194–2211 (2006), doi:10.1016/j.patcog.2006.04.018
Ma, Y.F., Hua, X.S., Lu, L., Zhang, H.J.: A generic framework of user attention model and its application in video summarization. IEEE Transactions on Multimedia 7(5), 907–919 (2005), doi:10.1109/TMM.2005.854410
Mahadevan, V., Vasconcelos, N.: Background subtraction in highly dynamic scenes. In: Preceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 1–6 (2008), doi:10.1109/CVPR.2008.4587576
McCoy, S., Everard, A., Polak, P., Galletta, D.F.: The effects of online advertising. ACM Communication 50(3), 84–88 (2007a), doi:10.1145/1226736.1226740
McCoy, S., Everard, A., Polak, P., Galletta, D.F.: Online ad intrusiveness. In: Jacko, J.A. (ed.) HCI 2007. LNCS, vol. 4553, pp. 86–89. Springer, Heidelberg (2007)
Mei, T., Hua, X.S., Yang, L., Li, S.: Videosense: Towards effective online video advertising. In: Proceedings of the 15th Annual ACM International Conference on Multimedia, MULTIMEDIA 2007, pp. 1075–1084. ACM, New York (2007), doi:10.1145/1291233.1291467
Siagian, C., Itti, L.: Rapid biologically-inspired scene classification using features shared with visual attention. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(2), 300–312 (2007), doi:10.1109/TPAMI.2007.40
Thawani, A., Gopalan, S., Sridhar, V.: Context aware personalized ad insertion in an interactive tv environment. In: Proceedings of Workshop on Personalization in Future TV (2004)
Wang, J., Fang, Y., Lu, H.: Online video advertising based on user’s attention relavancy computing. In: Preceedings of the IEEE International Conference on Multimedia and Expo, ICME, pp. 1161–1164 (2008), doi:10.1109/ICME.2008.4607646
Yang, R., Tian, Y., Huang, T.: Dct-based videoprinting on saliency-consistent regions for detecting video copies with text insertion. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds.) PCM 2009. LNCS, vol. 5879, pp. 797–806. Springer, Heidelberg (2009)
Zhu, G., Zheng, Y., Doermann, D., Jaeger, S.: Multi-scale structural saliency for signature detection. In: Preceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 1–8 (2007), doi:10.1109/CVPR.2007.383255
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Li, J., Gao, W. (2014). Saliency-Based Applications. In: Visual Saliency Computation. Lecture Notes in Computer Science, vol 8408. Springer, Cham. https://doi.org/10.1007/978-3-319-05642-5_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-05642-5_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05641-8
Online ISBN: 978-3-319-05642-5
eBook Packages: Computer ScienceComputer Science (R0)