Loading…
A Hierarchical Estimator for Object Tracking
A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independent...
Saved in:
Published in: | EURASIP journal on advances in signal processing 2010-01, Vol.2010 (1), Article 592960 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c405t-5e301cf8a50ef54436fd539772e9021be767724799438046dfd00a8a43ca20d3 |
---|---|
cites | cdi_FETCH-LOGICAL-c405t-5e301cf8a50ef54436fd539772e9021be767724799438046dfd00a8a43ca20d3 |
container_end_page | |
container_issue | 1 |
container_start_page | |
container_title | EURASIP journal on advances in signal processing |
container_volume | 2010 |
creator | Wu, Chin-Wen Chung, Yi-Nung Chung, Pau-Choo |
description | A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independently, the proposed approach combines local and global estimates into one for mutual compensation. Consequently, the Kalman-filter-based data fusion optimally adjusts the fusion gain based on environment conditions derived from each local estimator. The global estimation outputs are included in the local estimation process. Closed-loop mutual compensation between the local and global estimations is thus achieved to obtain higher tracking accuracy. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that the proposed approach successfully tracks objects. |
doi_str_mv | 10.1155/2010/592960 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_7980d17ecc2d4b91b85181140824ddf3</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_7980d17ecc2d4b91b85181140824ddf3</doaj_id><sourcerecordid>855688291</sourcerecordid><originalsourceid>FETCH-LOGICAL-c405t-5e301cf8a50ef54436fd539772e9021be767724799438046dfd00a8a43ca20d3</originalsourceid><addsrcrecordid>eNptkD1PwzAQhi0EEqUw8QeyMdDQs2M79lhVhSJV6tLdcvxREtKk2OnAv8clCDEwnO50evTe6UHoHsMTxozNCWCYM0kkhws0wVyUOccCLv_M1-gmxgaAcQJkgmaLbF27oIN5q41us1Uc6oMe-pD5VNuqcWbIdkGb97rb36Irr9vo7n76FO2eV7vlOt9sX16Xi01uKLAhZ64AbLzQDJxnlBbcW1bIsiROAsGVK3maaSklLQRQbr0F0ELTwmgCtpii1zHW9rpRx5AeCp-q17X6XvRhr3QYatM6VUoBFpfOGGJpJXElGBYYUxCEWuuLlPUwZh1D_3FycVCHOhrXtrpz_SkqwRgXgkicyMeRNKGPMTj_exmDOttVZ7tqtJvo2UjHRHV7F1TTn0KXrPyLfwFMO3aC</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>855688291</pqid></control><display><type>article</type><title>A Hierarchical Estimator for Object Tracking</title><source>Publicly Available Content Database</source><source>Springer Nature - SpringerLink Journals - Fully Open Access</source><creator>Wu, Chin-Wen ; Chung, Yi-Nung ; Chung, Pau-Choo</creator><creatorcontrib>Wu, Chin-Wen ; Chung, Yi-Nung ; Chung, Pau-Choo</creatorcontrib><description>A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independently, the proposed approach combines local and global estimates into one for mutual compensation. Consequently, the Kalman-filter-based data fusion optimally adjusts the fusion gain based on environment conditions derived from each local estimator. The global estimation outputs are included in the local estimation process. Closed-loop mutual compensation between the local and global estimations is thus achieved to obtain higher tracking accuracy. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that the proposed approach successfully tracks objects.</description><identifier>ISSN: 1687-6180</identifier><identifier>ISSN: 1687-6172</identifier><identifier>EISSN: 1687-6180</identifier><identifier>DOI: 10.1155/2010/592960</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Cameras ; Compensation ; Data integration ; Engineering ; Estimates ; Estimators ; Gain ; Optimization ; Quantum Information Technology ; Research Article ; Signal,Image and Speech Processing ; Spintronics ; Tracking ; Video Analysis for Human Behavior Understanding</subject><ispartof>EURASIP journal on advances in signal processing, 2010-01, Vol.2010 (1), Article 592960</ispartof><rights>Chin-Wen Wu et al. 2010. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c405t-5e301cf8a50ef54436fd539772e9021be767724799438046dfd00a8a43ca20d3</citedby><cites>FETCH-LOGICAL-c405t-5e301cf8a50ef54436fd539772e9021be767724799438046dfd00a8a43ca20d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925,37013</link.rule.ids></links><search><creatorcontrib>Wu, Chin-Wen</creatorcontrib><creatorcontrib>Chung, Yi-Nung</creatorcontrib><creatorcontrib>Chung, Pau-Choo</creatorcontrib><title>A Hierarchical Estimator for Object Tracking</title><title>EURASIP journal on advances in signal processing</title><addtitle>EURASIP J. Adv. Signal Process</addtitle><description>A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independently, the proposed approach combines local and global estimates into one for mutual compensation. Consequently, the Kalman-filter-based data fusion optimally adjusts the fusion gain based on environment conditions derived from each local estimator. The global estimation outputs are included in the local estimation process. Closed-loop mutual compensation between the local and global estimations is thus achieved to obtain higher tracking accuracy. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that the proposed approach successfully tracks objects.</description><subject>Cameras</subject><subject>Compensation</subject><subject>Data integration</subject><subject>Engineering</subject><subject>Estimates</subject><subject>Estimators</subject><subject>Gain</subject><subject>Optimization</subject><subject>Quantum Information Technology</subject><subject>Research Article</subject><subject>Signal,Image and Speech Processing</subject><subject>Spintronics</subject><subject>Tracking</subject><subject>Video Analysis for Human Behavior Understanding</subject><issn>1687-6180</issn><issn>1687-6172</issn><issn>1687-6180</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNptkD1PwzAQhi0EEqUw8QeyMdDQs2M79lhVhSJV6tLdcvxREtKk2OnAv8clCDEwnO50evTe6UHoHsMTxozNCWCYM0kkhws0wVyUOccCLv_M1-gmxgaAcQJkgmaLbF27oIN5q41us1Uc6oMe-pD5VNuqcWbIdkGb97rb36Irr9vo7n76FO2eV7vlOt9sX16Xi01uKLAhZ64AbLzQDJxnlBbcW1bIsiROAsGVK3maaSklLQRQbr0F0ELTwmgCtpii1zHW9rpRx5AeCp-q17X6XvRhr3QYatM6VUoBFpfOGGJpJXElGBYYUxCEWuuLlPUwZh1D_3FycVCHOhrXtrpz_SkqwRgXgkicyMeRNKGPMTj_exmDOttVZ7tqtJvo2UjHRHV7F1TTn0KXrPyLfwFMO3aC</recordid><startdate>20100101</startdate><enddate>20100101</enddate><creator>Wu, Chin-Wen</creator><creator>Chung, Yi-Nung</creator><creator>Chung, Pau-Choo</creator><general>Springer International Publishing</general><general>SpringerOpen</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope></search><sort><creationdate>20100101</creationdate><title>A Hierarchical Estimator for Object Tracking</title><author>Wu, Chin-Wen ; Chung, Yi-Nung ; Chung, Pau-Choo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c405t-5e301cf8a50ef54436fd539772e9021be767724799438046dfd00a8a43ca20d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Cameras</topic><topic>Compensation</topic><topic>Data integration</topic><topic>Engineering</topic><topic>Estimates</topic><topic>Estimators</topic><topic>Gain</topic><topic>Optimization</topic><topic>Quantum Information Technology</topic><topic>Research Article</topic><topic>Signal,Image and Speech Processing</topic><topic>Spintronics</topic><topic>Tracking</topic><topic>Video Analysis for Human Behavior Understanding</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Chin-Wen</creatorcontrib><creatorcontrib>Chung, Yi-Nung</creatorcontrib><creatorcontrib>Chung, Pau-Choo</creatorcontrib><collection>SpringerOpen</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Directory of Open Access Journals</collection><jtitle>EURASIP journal on advances in signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Chin-Wen</au><au>Chung, Yi-Nung</au><au>Chung, Pau-Choo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Hierarchical Estimator for Object Tracking</atitle><jtitle>EURASIP journal on advances in signal processing</jtitle><stitle>EURASIP J. Adv. Signal Process</stitle><date>2010-01-01</date><risdate>2010</risdate><volume>2010</volume><issue>1</issue><artnum>592960</artnum><issn>1687-6180</issn><issn>1687-6172</issn><eissn>1687-6180</eissn><abstract>A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independently, the proposed approach combines local and global estimates into one for mutual compensation. Consequently, the Kalman-filter-based data fusion optimally adjusts the fusion gain based on environment conditions derived from each local estimator. The global estimation outputs are included in the local estimation process. Closed-loop mutual compensation between the local and global estimations is thus achieved to obtain higher tracking accuracy. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that the proposed approach successfully tracks objects.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1155/2010/592960</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1687-6180 |
ispartof | EURASIP journal on advances in signal processing, 2010-01, Vol.2010 (1), Article 592960 |
issn | 1687-6180 1687-6172 1687-6180 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_7980d17ecc2d4b91b85181140824ddf3 |
source | Publicly Available Content Database; Springer Nature - SpringerLink Journals - Fully Open Access |
subjects | Cameras Compensation Data integration Engineering Estimates Estimators Gain Optimization Quantum Information Technology Research Article Signal,Image and Speech Processing Spintronics Tracking Video Analysis for Human Behavior Understanding |
title | A Hierarchical Estimator for Object Tracking |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T18%3A42%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Hierarchical%20Estimator%20for%20Object%20Tracking&rft.jtitle=EURASIP%20journal%20on%20advances%20in%20signal%20processing&rft.au=Wu,%20Chin-Wen&rft.date=2010-01-01&rft.volume=2010&rft.issue=1&rft.artnum=592960&rft.issn=1687-6180&rft.eissn=1687-6180&rft_id=info:doi/10.1155/2010/592960&rft_dat=%3Cproquest_doaj_%3E855688291%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c405t-5e301cf8a50ef54436fd539772e9021be767724799438046dfd00a8a43ca20d3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=855688291&rft_id=info:pmid/&rfr_iscdi=true |