Human posture recognition results using database A

Human Posture Recognition gives machines the ability to detect, track and identify people and their actions from video, has become a central topic in computer vision research. Recognition of human posture is a very challenging problem. The training and evaluation stage, datasets of pre-processed po...

Full description

Saved in:
Bibliographic Details
Main Authors: Htike, Kyaw Kyaw, Khalifa, Othman Omran, Lai, Weng Kin
Format: Book Chapter
Language:English
Published: IIUM Press 2011
Subjects:
Online Access:http://irep.iium.edu.my/21631/1/Chapter_7.pdf
http://irep.iium.edu.my/21631/
http://rms.research.iium.edu.my/bookstore/default.aspx
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.iium.irep.21631
record_format dspace
spelling my.iium.irep.216312020-10-30T00:12:57Z http://irep.iium.edu.my/21631/ Human posture recognition results using database A Htike, Kyaw Kyaw Khalifa, Othman Omran Lai, Weng Kin TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Human Posture Recognition gives machines the ability to detect, track and identify people and their actions from video, has become a central topic in computer vision research. Recognition of human posture is a very challenging problem. The training and evaluation stage, datasets of pre-processed posture images are needed. After the video sequences have been prepared, for the training and evaluation stage, they are pre-processed to produce three different types of datasets. This chapter will explain the results obtained using Dataset A. This dataset was obtained after pre-processing some of the video sequences that were taken at MIMOS building. In this dataset, there are six types of postures considered. The "unknown" posture was added so that during the training stage, the system could learn to differentiate postures which cannot be classified as belonging to any of the other types. This dataset is the main dataset for evaluating and comparing the performance (in terms of accuracy, i.e. recognition rate) of the different classifiers IIUM Press 2011 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/21631/1/Chapter_7.pdf Htike, Kyaw Kyaw and Khalifa, Othman Omran and Lai, Weng Kin (2011) Human posture recognition results using database A. In: Human Behaviour Recognition, Identification and Computer Interaction. IIUM Press, Kuala Lumpur, pp. 49-57. ISBN 978-967-418-156-7 http://rms.research.iium.edu.my/bookstore/default.aspx
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
spellingShingle TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Htike, Kyaw Kyaw
Khalifa, Othman Omran
Lai, Weng Kin
Human posture recognition results using database A
description Human Posture Recognition gives machines the ability to detect, track and identify people and their actions from video, has become a central topic in computer vision research. Recognition of human posture is a very challenging problem. The training and evaluation stage, datasets of pre-processed posture images are needed. After the video sequences have been prepared, for the training and evaluation stage, they are pre-processed to produce three different types of datasets. This chapter will explain the results obtained using Dataset A. This dataset was obtained after pre-processing some of the video sequences that were taken at MIMOS building. In this dataset, there are six types of postures considered. The "unknown" posture was added so that during the training stage, the system could learn to differentiate postures which cannot be classified as belonging to any of the other types. This dataset is the main dataset for evaluating and comparing the performance (in terms of accuracy, i.e. recognition rate) of the different classifiers
format Book Chapter
author Htike, Kyaw Kyaw
Khalifa, Othman Omran
Lai, Weng Kin
author_facet Htike, Kyaw Kyaw
Khalifa, Othman Omran
Lai, Weng Kin
author_sort Htike, Kyaw Kyaw
title Human posture recognition results using database A
title_short Human posture recognition results using database A
title_full Human posture recognition results using database A
title_fullStr Human posture recognition results using database A
title_full_unstemmed Human posture recognition results using database A
title_sort human posture recognition results using database a
publisher IIUM Press
publishDate 2011
url http://irep.iium.edu.my/21631/1/Chapter_7.pdf
http://irep.iium.edu.my/21631/
http://rms.research.iium.edu.my/bookstore/default.aspx
_version_ 1683230265200082944
score 13.211869