Loading…

Indoor human tracking application using multiple depth-cameras

This research developed an application that could tracks and locates human's presence and position in indoor environment using multiple depth-cameras. Kinect as the most affordable device that equipped with depth-camera was used in this work. The application obtains stream data from Kinect and...

Full description

Saved in:
Bibliographic Details
Main Authors: Saputra, M. R. U., Widyawan, W., Putra, G. D., Santosa, P. I.
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 312
container_issue
container_start_page 307
container_title
container_volume
creator Saputra, M. R. U.
Widyawan, W.
Putra, G. D.
Santosa, P. I.
description This research developed an application that could tracks and locates human's presence and position in indoor environment using multiple depth-cameras. Kinect as the most affordable device that equipped with depth-camera was used in this work. The application obtains stream data from Kinect and analyzes presence of human using skeletal tracking library on Kinect for Windows SDK v1. The final application also visualizes human location on 3D environment using Windows Presentation Foundation (WPF) 4.0. In order to visualize 3D object correctly, the application also took into account the coverage that may intersect when two Kinects were placed in adjacent position so that the final human location is combined. In the end, application was tested in 3 different scenarios and it's found that the average error in determining human location was 0.13589 meters.
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6468750</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6468750</ieee_id><sourcerecordid>6468750</sourcerecordid><originalsourceid>FETCH-LOGICAL-i105t-c340f52e0825250e3c087b73300f3a416b862685bd282a892b130dd1eaec66093</originalsourceid><addsrcrecordid>eNotjstKAzEUQAMiqLVf0E1-YODmdSfdCFJ8FArd6LrcSe600XmRySz8eym6OnAWh3MjHpTF2hjQaO_Eep6_AEApQIV4L572QxzHLC9LT4MsmcJ3Gs6SpqlLgUoaB7nMV9MvXUlTxzLyVC5VoJ4zzY_itqVu5vU_V-Lz9eVj914djm_73fOhSgpcqYKx0DrN4LXTDtgE8HVznYLWkFXYeNToXRO11-S3ulEGYlRMHBBha1Zi89dNzHyacuop_5zQoq8dmF8mAUD0</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Indoor human tracking application using multiple depth-cameras</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Saputra, M. R. U. ; Widyawan, W. ; Putra, G. D. ; Santosa, P. I.</creator><creatorcontrib>Saputra, M. R. U. ; Widyawan, W. ; Putra, G. D. ; Santosa, P. I.</creatorcontrib><description>This research developed an application that could tracks and locates human's presence and position in indoor environment using multiple depth-cameras. Kinect as the most affordable device that equipped with depth-camera was used in this work. The application obtains stream data from Kinect and analyzes presence of human using skeletal tracking library on Kinect for Windows SDK v1. The final application also visualizes human location on 3D environment using Windows Presentation Foundation (WPF) 4.0. In order to visualize 3D object correctly, the application also took into account the coverage that may intersect when two Kinects were placed in adjacent position so that the final human location is combined. In the end, application was tested in 3 different scenarios and it's found that the average error in determining human location was 0.13589 meters.</description><identifier>ISBN: 1467330264</identifier><identifier>ISBN: 9781467330268</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cameras ; Data visualization ; Hardware ; Humans ; Indoor environments ; Servers ; Skeleton</subject><ispartof>2012 International Conference on Advanced Computer Science and Information Systems (ICACSIS), 2012, p.307-312</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6468750$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6468750$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Saputra, M. R. U.</creatorcontrib><creatorcontrib>Widyawan, W.</creatorcontrib><creatorcontrib>Putra, G. D.</creatorcontrib><creatorcontrib>Santosa, P. I.</creatorcontrib><title>Indoor human tracking application using multiple depth-cameras</title><title>2012 International Conference on Advanced Computer Science and Information Systems (ICACSIS)</title><addtitle>ICACSIS</addtitle><description>This research developed an application that could tracks and locates human's presence and position in indoor environment using multiple depth-cameras. Kinect as the most affordable device that equipped with depth-camera was used in this work. The application obtains stream data from Kinect and analyzes presence of human using skeletal tracking library on Kinect for Windows SDK v1. The final application also visualizes human location on 3D environment using Windows Presentation Foundation (WPF) 4.0. In order to visualize 3D object correctly, the application also took into account the coverage that may intersect when two Kinects were placed in adjacent position so that the final human location is combined. In the end, application was tested in 3 different scenarios and it's found that the average error in determining human location was 0.13589 meters.</description><subject>Cameras</subject><subject>Data visualization</subject><subject>Hardware</subject><subject>Humans</subject><subject>Indoor environments</subject><subject>Servers</subject><subject>Skeleton</subject><isbn>1467330264</isbn><isbn>9781467330268</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjstKAzEUQAMiqLVf0E1-YODmdSfdCFJ8FArd6LrcSe600XmRySz8eym6OnAWh3MjHpTF2hjQaO_Eep6_AEApQIV4L572QxzHLC9LT4MsmcJ3Gs6SpqlLgUoaB7nMV9MvXUlTxzLyVC5VoJ4zzY_itqVu5vU_V-Lz9eVj914djm_73fOhSgpcqYKx0DrN4LXTDtgE8HVznYLWkFXYeNToXRO11-S3ulEGYlRMHBBha1Zi89dNzHyacuop_5zQoq8dmF8mAUD0</recordid><startdate>201212</startdate><enddate>201212</enddate><creator>Saputra, M. R. U.</creator><creator>Widyawan, W.</creator><creator>Putra, G. D.</creator><creator>Santosa, P. I.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201212</creationdate><title>Indoor human tracking application using multiple depth-cameras</title><author>Saputra, M. R. U. ; Widyawan, W. ; Putra, G. D. ; Santosa, P. I.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i105t-c340f52e0825250e3c087b73300f3a416b862685bd282a892b130dd1eaec66093</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Cameras</topic><topic>Data visualization</topic><topic>Hardware</topic><topic>Humans</topic><topic>Indoor environments</topic><topic>Servers</topic><topic>Skeleton</topic><toplevel>online_resources</toplevel><creatorcontrib>Saputra, M. R. U.</creatorcontrib><creatorcontrib>Widyawan, W.</creatorcontrib><creatorcontrib>Putra, G. D.</creatorcontrib><creatorcontrib>Santosa, P. I.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library Online</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Saputra, M. R. U.</au><au>Widyawan, W.</au><au>Putra, G. D.</au><au>Santosa, P. I.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Indoor human tracking application using multiple depth-cameras</atitle><btitle>2012 International Conference on Advanced Computer Science and Information Systems (ICACSIS)</btitle><stitle>ICACSIS</stitle><date>2012-12</date><risdate>2012</risdate><spage>307</spage><epage>312</epage><pages>307-312</pages><isbn>1467330264</isbn><isbn>9781467330268</isbn><abstract>This research developed an application that could tracks and locates human's presence and position in indoor environment using multiple depth-cameras. Kinect as the most affordable device that equipped with depth-camera was used in this work. The application obtains stream data from Kinect and analyzes presence of human using skeletal tracking library on Kinect for Windows SDK v1. The final application also visualizes human location on 3D environment using Windows Presentation Foundation (WPF) 4.0. In order to visualize 3D object correctly, the application also took into account the coverage that may intersect when two Kinects were placed in adjacent position so that the final human location is combined. In the end, application was tested in 3 different scenarios and it's found that the average error in determining human location was 0.13589 meters.</abstract><pub>IEEE</pub><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 1467330264
ispartof 2012 International Conference on Advanced Computer Science and Information Systems (ICACSIS), 2012, p.307-312
issn
language eng
recordid cdi_ieee_primary_6468750
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Cameras
Data visualization
Hardware
Humans
Indoor environments
Servers
Skeleton
title Indoor human tracking application using multiple depth-cameras
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T22%3A48%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Indoor%20human%20tracking%20application%20using%20multiple%20depth-cameras&rft.btitle=2012%20International%20Conference%20on%20Advanced%20Computer%20Science%20and%20Information%20Systems%20(ICACSIS)&rft.au=Saputra,%20M.%20R.%20U.&rft.date=2012-12&rft.spage=307&rft.epage=312&rft.pages=307-312&rft.isbn=1467330264&rft.isbn_list=9781467330268&rft_id=info:doi/&rft_dat=%3Cieee_6IE%3E6468750%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i105t-c340f52e0825250e3c087b73300f3a416b862685bd282a892b130dd1eaec66093%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6468750&rfr_iscdi=true