Acoustic fall detection using Gaussian mixture models and GMM supervectors

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2009, Pages 69-72

  Zhuang, Xiaodan ^a   Huang, Jing ^b   Potamianos, Gerasimos ^b,c   Hasegawa Johnson, Mark ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

^c INSTITUTE OF INFORMATICS AND TELECOMMUNICATIONS   (Greece)

Author keywords

Fall detection; Gaussian mixture model; GMM supervector; Support vector machine

Indexed keywords

AUDIO SIGNAL; DATA SETS; EUCLIDEAN DISTANCE MEASURE; F-SCORE; FALL DETECTION; FAR-FIELD; GAUSSIAN MIXTURE MODEL; GMM SUPERVECTOR; HOME ENVIRONMENT; POST PROCESSING; SUPERVECTOR; SYSTEM MODELS;

BLIND SOURCE SEPARATION; COMMUNICATION CHANNELS (INFORMATION THEORY); IMAGE RETRIEVAL; IMAGE SEGMENTATION; MAGNETOSTRICTIVE DEVICES; MIXTURES; MODEL STRUCTURES; OBJECT RECOGNITION; SIGNAL DETECTION; SIGNAL PROCESSING; SPEECH RECOGNITION; SUPPORT VECTOR MACHINES; SYSTEMS ENGINEERING;

AUDIO ACOUSTICS;

EID: 70349200911     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2009.4959522     Document Type: Conference Paper

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