De Xu

Publications (7)0 Total impact

• Source

  Available from: usf.edu

  Conference Proceeding: Automatic video annotation with adaptive number of key words

  Fangshi Wang, Wei Lu, Jingen Liu, M. Shah, De Xu
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  ABSTRACT: Retrieving videos using key words requires obtaining the semantic features of the videos. Most work reported in the literature focuses on annotating a video shot with a fixed number of key words, no matter how much information is contained in the video shot. In this paper, we propose a new approach to automatically annotate a video shot with an adaptive number of annotation key words according to the richness of the video content. A semantic candidate set (SCS) with fixed size is discovered using visual features. Then the final annotation set, which has an unfixed number of key words, is obtained from the SCS by using Bayesian inference, which combines static and dynamic inference to remove the irrelevant candidate key words. We have applied our approach to video retrieval. The experiments demonstrate that video retrieval using our annotation approach outperforms retrieval using a fixed number of annotation words.
  Pattern Recognition, 2008. ICPR 2008. 19th International Conference on; 01/2009
• Conference Proceeding: SS-ClusterTree: a subspace clustering based indexing algorithm over high-dimensional image features.

  Hongli Xu, Dantong Yu, De Xu, Aidong Zhang
  Proceedings of the 7th ACM International Conference on Image and Video Retrieval, CIVR 2008, Niagara Falls, Canada, July 7-9, 2008; 01/2008
• Conference Proceeding: Automatic Video Annotation and Retrieval Based on Bayesian Inference.

  Fangshi Wang, De Xu, Wei Lu, Weixin Wu
  Advances in Multimedia Modeling, 13th International Multimedia Modeling Conference, MMM 2007, Singapore, January 9-12, 2007. Proceedings, Part I; 01/2007
• Conference Proceeding: An Applicable Hierarchical Clustering Algorithm for Content-Based Image Retrieval.

  Hongli Xu, De Xu, Enai Lin
  Computer Vision/Computer Graphics Collaboration Techniques, Third International Conference, MIRAGE 2007, Rocquencourt, France, March 28-30, 2007, Proceedings; 01/2007
• Conference Proceeding: User-Centered Image Semantics Classification.

  Hongli Xu, De Xu, Fangshi Wang
  Advanced Data Mining and Applications, Second International Conference, ADMA 2006, Xi'an, China, August 14-16, 2006, Proceedings; 01/2006
• Conference Proceeding: Automatic Annotation and Retrieval for Videos.

  Fangshi Wang, De Xu, Wei Lu, Hongli Xu
  Advances in Image and Video Technology, First Pacific Rim Symposium, PSIVT 2006, Hsinchu, Taiwan, December 10-13, 2006, Proceedings; 01/2006
• Chapter: Application of Bayesian Inference to Automatic Semantic Annotation of Videos

  Fangshi Wang, De Xu, Hongli Xu, Wei Lu, Weixin Wu
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  ABSTRACT: Summary. It is an important task to automatically extract semantic annotation of a video shot. This high level semantic information can improve the performance of video retrieval. In this paper, we propose a novel approach to annotate a new video shot automatically with a non-fixed number of concepts. The process is carried out by three steps. Firstly, the semantic importance degree (SID)is introduced and a simple method is proposed to extract the semantic candidate set (SCS) under considering SID of several concepts co-occurring in the same shot. Secondly, a semantic network is constructed using an improved K2 algorithm. Finally, the final annotation set is chosen by Bayesian inference. Experimental results show that the performance of automatically annotating a new video shot is significantly improved using our method, compared with classical classifiers such as Naïve Bayesian and K Nearest Neighbor.
  01/1970: pages 447-466;