Comparison between genetic algorithms and the Baum-Welch algorithm in learning HMMs for human activity classification

Óscar Pérez*, Massimo Piccardi, Jesús García, Miguel A. Patricio, José M. Molina

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

15 Citations (Scopus)

Abstract

A Hidden Markov Model (HMM) is used as an efficient and robust technique for human activities classification. The HMM evaluates a set of video recordings to classify each scene as a function of the future, actual and previous scenes. The probabilities of transition between states of the HMM and the observation model should be adjusted in order to obtain a correct classification. In this work, these matrixes are estimated using the well known Baum-Welch algorithm that is based on the definition of the real observations as a mixture of two Gaussians for each state. The application of the GA follows the same principle but the optimization is carried out considering the classification. In this case, GA optimizes the Gaussian parameters considering as a fitness function the results of the classification application. Results show the improvement of GA techniques for human activities recognition.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computing
Subtitle of host publicationEvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG, Proceedings
EditorsMario Giacobini
Place of PublicationBerlin
PublisherSpringer, Springer Nature
Pages399-406
Number of pages8
ISBN (Electronic)9783540718055
ISBN (Print)3540718044, 9783540718048
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventEvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG - Valencia, Spain
Duration: 11 Apr 200713 Apr 2007

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume4448
ISSN (Print)0302-9743

Other

OtherEvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG
Country/TerritorySpain
CityValencia
Period11/04/0713/04/07

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