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Exemplar-SVM for Action Recognition

Exemplar-SVM for Action Recognition. Week 11 Presented by Christina Peterson. Changes made to Combined Exemplar-SVMs. Multi-Class SVM trained on calibrated exemplar scores rather than raw exemplar- svm scores Ran STIP for Kicking action class to obtain descriptors for more frames.

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Exemplar-SVM for Action Recognition

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  1. Exemplar-SVM for Action Recognition Week 11 Presented by Christina Peterson

  2. Changes made to Combined Exemplar-SVMs • Multi-Class SVM trained on calibrated exemplar scores rather than raw exemplar-svm scores • Ran STIP for Kicking action class to obtain descriptors for more frames

  3. Recognition Accuracies on UCF Sports data set • Combined Exemplar-SVMs increased from 67.3% accuracy to 75% accuracy

  4. Confusion Matrix: Combined Exemplar-SVM Di Go Ki Li Ho Ru Sk Sb Ss Wa Diving Golf Kick Lift Horse-Ride Run Skateboard Swing-bench Swing-side Walk

  5. Conclusions • The changes have made performance comparable to Standard Multi-Class SVM • The selected exemplar set has a large impact on the accuracy on the test set • Improving accuracy would involve manually selecting the best exemplars to represent the action class

  6. References [1] M. D. Rodriguez, J. Ahmed, and M. Shah. Action mach: A spatio-temporal maximum average correlation height filter for action recognition. In CVPR, 2008. [2] Yeffet and L. Wolf. Local trinary patterns for human action recognition. In ICCV, 2009. [3] H. Wang, M. Ullah, A. Klaser, I. Laptev, and C. Schmid. Evaluation of local spatio-temporal features for action recognition. In BMVC, 2009. [4] Q. Le, W. Zou, S. Yeung, and A. Ng. Learning hierarchical invariant spatiotemporal features for action recognition with independent subspace analysis. In CVPR, 2011. [5] A. Kovashka and K. Grauman. Learning a hierarchy of discriminative spacetime neighborhood features for human action recognition. InCVPR, 2010. [6] X. Wu, D. Xu, L. Duan, and J. Luo. Action recognition using context and appearance distribution features. InCVPR, 2011. [7] S. Sadanand and J. J. Corso. Action bank: A high-level representation of activity in video. CVPR, 2012.

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