Abstract
Anchor shot detection is a challenging and important task for news video analysis. This paper has put forward a novel anchor shot detection algorithm for the situations with dynamic studio background and multiple anchorpersons based on spatio-temporal slice analysis. Firstly, two different diagonal spatio-temporal slices are extracted and divided into three portions, after which sequential clustering is adopted to classify all slices from two sliding windows obtained from each shot to get the candidate anchor shots. And finally, structure tensor is employed, combining with the distribution properties to precisely detect the real anchor shots. Experimental results on seven different styles of news programs demonstrate that our algorithm is effective toward the situations described above. And the usage of spatio-temporal slice can also reduce the computational complexity.
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References
Zhang, H., Gong, Y., Smoliar, S., et al.: Automatic Parsing of News Video. In: Proceedings of the International Conference on Multimedia Computing and Systems, Boston, MA, pp. 45–54 (1994)
Ma, Y., Bai, X., Xu, G., et al.: Research on Anchorperson Detection Method in News Video. Chinese Journal of Software 12, 377–382 (2001)
Xu, D., Li, X., Liu, Z., Yuan, Y.: Anchorperson Extraction for Picture in Picture News Video. Pattern Recogn. Lett. 25, 1587–1594 (2004)
Zheng, F., Li, S., Li, H., et al.: Weighted Block Matching-based Anchor Shot Detection with Dynamic Background. In: Proceeding of International Conference on Image Analysis and Recognition, pp. 220–228 (2009)
Xinbo, G., Xiaoou, T.: Unsupervised Video-shot Segmentation and Model-free Anchorperson Detection for News Video Story Parsing. IEEE Transactions on Circuits and Systems for Video Technology 12, 765–776 (2002)
D’Anna, L., Percannella, G., Sansone, C., Vento, M.: A Multi-Stage Approach for News Video Segmentation Based on Automatic Anchorperson Number Detection. In: Proceedings of International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, pp. 229–234 (2007)
Lan, D., Ma, Y., Zhang, H.: Multi-level Anchorperson Detection Using Multimodal Association. In: Proceedings of the 17th International Conference on Pattern Recognition, pp. 890–893 (2004)
Santo, M., De, F.P., Percannella, G., et al.: An Unsupervised Algorithm for Anchor Shot Detection. In: Proceedings of the 18th International Conference on Pattern Recognition, pp. 1238–1241 (2006)
Anan, L., Sheng, T., Yongdong, Z., et al.: A Novel Anchorperson Detection Algorithm Based on Spatio-temporal Slice. In: Proceedings of International Conference on Image Analysis and Processing, pp. 371–375 (2007)
Chong-Wah, N., Ting-Chuen, P., Hong-Jiang, Z.: Motion Analysis and Segmentation through Spatio-temporal Slices Processing. IEEE Transactions on Image Processing 12, 341–355 (2003)
De Santo, M., Percannella, G., Sansone, C., et al.: Combining Experts for Anchorperson Shot Detection in News Videos. Pattern Analysis & Application 7, 447–460 (2004)
Bertini, M., Del Bimbo, A., Pala, P.: Content-based Indexing and Retrieval of TV News. Pattern Recognition Letter 22, 503–516 (2001)
Hanjalic, A., Lagendijk, R.L., Biemond, J.: Semi-automatic News Analysis, Indexing and Classification System Based on Topics Preselection. In: Proceedings of SPIE: Electronic Imaging: Storage and Retrieval of Image and Video Databases, San Jose (1999)
Theodoridis, S., Koutroumbas, K.: Pattern Recognition, 2nd edn. Academic Press, London (2003)
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Zheng, F., Li, S., Wu, H., Feng, J. (2010). Anchor Shot Detection with Diverse Style Backgrounds Based on Spatial-Temporal Slice Analysis. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_68
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DOI: https://doi.org/10.1007/978-3-642-11301-7_68
Publisher Name: Springer, Berlin, Heidelberg
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