Human Body Motions Classifications

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A03148635" target="_blank" >RIV/68407700:21230/08:03148635 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Human Body Motions Classifications

Original language description

This paper deals with video based parameterization and classification of human body motions. The main task of this work is to develop and verify the procedures for observing of muscle and brain activity. The developed procedures have no negative impact to brain activity (the tracking does not affect the measured EEG signals). The procedures required only standard hardware equipment accessible on neurological laboratories. The body motions are non-contact sensed using a pair of standard DV camcorders. This work includes the description of observing, discerning and parameterization procedures and the discussion of motion classification. The set of classifiers - hierarchical clustering algorithm, recursive clustering algorithm, k-means classifier, Bayes classifier and classifier based on discrimination functions - was developed and implemented. The analysis of the classifiers properties was accomplished in this work. The accuracy of classification was tested for selected

Czech name

Human Body Motions Classifications

Czech description

This paper deals with video based parameterization and classification of human body motions. The main task of this work is to develop and verify the procedures for observing of muscle and brain activity. The developed procedures have no negative impact to brain activity (the tracking does not affect the measured EEG signals). The procedures required only standard hardware equipment accessible on neurological laboratories. The body motions are non-contact sensed using a pair of standard DV camcorders. This work includes the description of observing, discerning and parameterization procedures and the discussion of motion classification. The set of classifiers - hierarchical clustering algorithm, recursive clustering algorithm, k-means classifier, Bayes classifier and classifier based on discrimination functions - was developed and implemented. The analysis of the classifiers properties was accomplished in this work. The accuracy of classification was tested for selected

Type

D - Article in proceedings

CEP classification

JA - Electronics and optoelectronics

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2008

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

IFMBE Proceedings

ISBN

978-3-540-89207-6

ISSN

1680-0737

e-ISSN

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Number of pages

4

Pages from-to

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Publisher name

Springer

Place of publication

Berlin

Event location

Antwerp

Event date

Nov 23, 2008

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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