Publication Type : Journal Article
Publisher : THUMOS Challenge: Action Recognition with a Large Number of Classes
Source : THUMOS Challenge: Action Recognition with a Large Number of Classes (2014)
Url : http://crcv.ucf.edu/THUMOS14/papers/Univ%20of%20Canberra-HCC.pdf
Keywords : Action recognition, dense trajectories, Fisher vector, PCA
Campus : Coimbatore
School : School of Engineering
Department : Electrical and Electronics
Year : 2014
Abstract : We basically use a Bag-of-Words framework. We compute the improved dense trajectories to compute Fisher vectors that serve as features. Using the training videos, we compute a mapping function which we conjecture to contain the principal information about each action. Given a temporally untrimmed video, we project it’s feature along this mapping. The transformed features are passed to 1-vs all SVM classifiers framework to get the prediction score of each actions in the given video clip.
Cite this Research Publication : Dr. Oruganti Venkata Ramana Murthy and Goecke, R., “Uc–hcc submission to thumos 2014”, THUMOS Challenge: Action Recognition with a Large Number of Classes, 2014.