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» Image Distance Using Hidden Markov Models
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ICIAP
2009
ACM
14 years 8 months ago
A New Generative Feature Set Based on Entropy Distance for Discriminative Classification
Abstract. Score functions induced by generative models extract fixeddimensions feature vectors from different-length data observations by subsuming the process of data generation, ...
Alessandro Perina, Marco Cristani, Umberto Castell...
DATAMINE
2006
83views more  DATAMINE 2006»
13 years 7 months ago
Structural Hidden Markov Models Using a Relation of Equivalence: Application to Automotive Designs
Standard hidden Markov models (HMM's) have been studied extensively in the last two decades. It is well known that these models assume state conditional independence of the ob...
Djamel Bouchaffra, Jun Tan
IBPRIA
2007
Springer
14 years 1 months ago
HMM-Based Action Recognition Using Contour Histograms
This paper describes an experimental study about a robust contour feature (shape-context) for using in action recognition based on continuous hidden Markov models (HMM). We ran dif...
Maria Ángeles Mendoza, Nicolas Pérez...
ICPR
2010
IEEE
13 years 7 months ago
High-Level Feature Extraction Using SIFT GMMs and Audio Models
—We propose a statistical framework for high-level feature extraction that uses SIFT Gaussian mixture models (GMMs) and audio models. SIFT features were extracted from all the im...
Nakamasa Inoue, Tatsuhiko Saito, Koichi Shinoda, S...
ICIAP
2007
ACM
14 years 7 months ago
Sparseness Achievement in Hidden Markov Models
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
Manuele Bicego, Marco Cristani, Vittorio Murino