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In this paper, we present a novel bilinear invariant representation for video classification and retrieval. We rely on the kernel space in functional analysis to formulate a general invariants theory. We show that null-space invariants is a special case of the general theory when the transformation is linear. Subsequently, we derive an invariant basis representation for bilinear transformations. We...
View-invariant representation has been shown to be a powerful tool in classification and retrieval of motion events due to camera motions. Traditional null space representation is invariant only for linear transformations and does not yield high accuracy for camera with non-linear motions. In this paper, we propose a novel general framework for non-linear kernel space invariant representation (NKSI),...
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