Automatic Video Genre Categorization using Hierarchical SVM

@article{Yuan2006AutomaticVG,
  title={Automatic Video Genre Categorization using Hierarchical SVM},
  author={Xun Yuan and Wei Lai and Tao Mei and Xian-Sheng Hua and Xiuqing Wu and Shipeng Li},
  journal={2006 International Conference on Image Processing},
  year={2006},
  pages={2905-2908}
}
This paper presents an automatic video genre categorization scheme based on the hierarchical ontology on video genres. Ten computable spatio-temporal features are extracted to distinguish the different genres using a hierarchical support vector machines (SVM) classifier built by cross-validation, which consists of a series of SVM classifiers united in a binary-tree form. As the order and genre partition strategy of the SVM classifier series affect the over performance of the united classifier… CONTINUE READING
Highly Influential
This paper has highly influenced 10 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 117 citations. REVIEW CITATIONS
76 Citations
10 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 76 extracted citations

118 Citations

0102030'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 118 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…