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...

Full description

Saved in:
Bibliographic Details
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
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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:10.1109/WAC.2002.1049575