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A Similarity Measure Between Vector Sequences with Application to Handwritten Word Image Retrieval

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A Similarity Measure Between Vector Sequences with Application to Handwritten Word Image Retrieval
This article proposes a novel similarity measure between vector sequences. Recently, a model-based approach was introduced to address this issue. It consists in modeling each sequence with a continuousHiddenMarkovModel (CHMM) and computing a probabilistic measure of similarity between C-HMMs. In this paper we propose to model sequences with semi-continuous HMMs (SC-HMMs): the Gaussians of the SC-HMMs are constrained to belong to a shared pool of Gaussians. This constraint provides two major benefits. First, the a priori information contained in the common set of Gaussians leads to a more accurate estimate of the HMM parameters. Second, the computation of a probabilistic similarity between two SC-HMMs can be simplified to a Dynamic Time Warping (DTW) between their mixture weight vectors, which reduces significantly the computational cost. Experimental results on a handwritten word retrieval task show that the proposed similarity outperforms the traditional DTW between t...
José A. Rodríguez-Serrano, Florent P
Added 09 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors José A. Rodríguez-Serrano, Florent Perronnin, Josep Lladós, Gemma Sánchez
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