Hidden Markov models for silhouette classification

In this paper, a new technique for object classification from silhouettes is presented. Hidden Markov models are used as a classification mechanism. Through a set of experiments, we show the validity of our approach and show its invariance under severe rotation conditions. Also, a comparison with ot...

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Main Authors: Abd-Almageed, W., Smith, C.
Format: Conference Proceeding
Language:English
Subjects:
Computer vision
Feature extraction
Fourier transforms
Hidden Markov models
Neural networks
Parameter estimation
Pattern recognition
Probability distribution
Shape measurement
Wavelet transforms
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Smith, C.
description In this paper, a new technique for object classification from silhouettes is presented. Hidden Markov models are used as a classification mechanism. Through a set of experiments, we show the validity of our approach and show its invariance under severe rotation conditions. Also, a comparison with other techniques that use hidden Markov models for object classification from silhouettes is presented.
doi_str_mv 10.1109/WAC.2002.1049575
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subjects Computer vision
Feature extraction
Fourier transforms
Hidden Markov models
Neural networks
Parameter estimation
Pattern recognition
Probability distribution
Shape measurement
Wavelet transforms
title Hidden Markov models for silhouette classification
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