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CVPR
2010
IEEE

Action Classification on Product Manifolds

13 years 8 months ago
Action Classification on Product Manifolds
Videos can be naturally represented as multidimensional arrays known as tensors. However, the geometry of the tensor space is often ignored. In this paper, we argue that the underlying geometry of the tensor space is an important property for action classification. We characterize a tensor as a point on a product manifold and perform classification on this space. First, we factorize a tensor relating to each order using a modified High Order Singular Value Decomposition (HOSVD). We recognize each factorized space as a Grassmann manifold. Consequently, a tensor is mapped to a point on a product manifold and the geodesic distance on a product manifold is computed for tensor classification. We assess the proposed method using two public video databases, namely Cambridge-Gesture gesture and KTH human action data sets. Experimental results reveal that the proposed method performs very well on these data sets. In addition, our method is generic in the sense that no prior training is needed....
Yui Man Lui, J Ross Beveridge, Michael Kirby
Added 02 Aug 2010
Updated 02 Aug 2010
Type Conference
Year 2010
Where CVPR
Authors Yui Man Lui, J Ross Beveridge, Michael Kirby
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