Semantic Model Vectors for Complex Video Event Recognition
@article{Merler2012SemanticMV, title={Semantic Model Vectors for Complex Video Event Recognition}, author={Michele Merler and Bert Huang and Lexing Xie and Gang Hua and A. Natsev}, journal={IEEE Transactions on Multimedia}, year={2012}, volume={14}, pages={88-101} }
We propose semantic model vectors, an intermediate level semantic representation, as a basis for modeling and detecting complex events in unconstrained real-world videos, such as those from YouTube. The semantic model vectors are extracted using a set of discriminative semantic classifiers, each being an ensemble of SVM models trained from thousands of labeled web images, for a total of 280 generic concepts. Our study reveals that the proposed semantic model vectors representation outperforms… CONTINUE READING
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