A Space-Mapping Method for Object Location Estimation Adaptive to Camera Setup Changes for Vision-Based Automation Applications
A new space-mapping method for object location estimation, which is adaptive to camera setup changes, for use in various automation applications is proposed. The location of an object appearing in an image is estimated by mapping image coordinates of object points to corresponding real-world coordin...
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| Veröffentlicht in: | IEEE transactions on circuits and systems for video technology 2012-01, Vol.22 (1), p.157-162 |
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| container_title | IEEE transactions on circuits and systems for video technology |
| container_volume | 22 |
| creator | WU, Chih-Jen TSAI, Wen-Hsiang |
| description | A new space-mapping method for object location estimation, which is adaptive to camera setup changes, for use in various automation applications is proposed. The location of an object appearing in an image is estimated by mapping image coordinates of object points to corresponding real-world coordinates using a mapping table, which is constructed in two stages, with the first stage for establishing a basic table using bilinear interpolation in the camera manufacturing environment and the second for adapting the table to changes of camera heights and orientations in the application field. Analytic equations for table adaptation are derived by skillful utilization of both image formation and camera geometry properties. Good experimental results are shown to prove the feasibility of the proposed method. |
| doi_str_mv | 10.1109/TCSVT.2011.2157196 |
| format | Article |
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The location of an object appearing in an image is estimated by mapping image coordinates of object points to corresponding real-world coordinates using a mapping table, which is constructed in two stages, with the first stage for establishing a basic table using bilinear interpolation in the camera manufacturing environment and the second for adapting the table to changes of camera heights and orientations in the application field. Analytic equations for table adaptation are derived by skillful utilization of both image formation and camera geometry properties. Good experimental results are shown to prove the feasibility of the proposed method.</description><identifier>ISSN: 1051-8215</identifier><identifier>EISSN: 1558-2205</identifier><identifier>DOI: 10.1109/TCSVT.2011.2157196</identifier><identifier>CODEN: ITCTEM</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Applied sciences ; Artificial intelligence ; Automation ; Calibration ; Camera setup changes ; Cameras ; Computer science; control theory; systems ; Estimation ; Exact sciences and technology ; Floors ; Image processing ; Information, signal and communications theory ; Interpolation ; Lenses ; Mapping ; Mathematical analysis ; Mobile robots ; object location estimation ; Optical imaging ; Pattern recognition ; Pattern recognition. Digital image processing. 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The location of an object appearing in an image is estimated by mapping image coordinates of object points to corresponding real-world coordinates using a mapping table, which is constructed in two stages, with the first stage for establishing a basic table using bilinear interpolation in the camera manufacturing environment and the second for adapting the table to changes of camera heights and orientations in the application field. Analytic equations for table adaptation are derived by skillful utilization of both image formation and camera geometry properties. Good experimental results are shown to prove the feasibility of the proposed method.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Calibration</subject><subject>Camera setup changes</subject><subject>Cameras</subject><subject>Computer science; control theory; systems</subject><subject>Estimation</subject><subject>Exact sciences and technology</subject><subject>Floors</subject><subject>Image processing</subject><subject>Information, signal and communications theory</subject><subject>Interpolation</subject><subject>Lenses</subject><subject>Mapping</subject><subject>Mathematical analysis</subject><subject>Mobile robots</subject><subject>object location estimation</subject><subject>Optical imaging</subject><subject>Pattern recognition</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Position (location)</subject><subject>Signal processing</subject><subject>space mapping</subject><subject>table adaptation</subject><subject>Tables (data)</subject><subject>Telecommunications and information theory</subject><issn>1051-8215</issn><issn>1558-2205</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkUFv1DAQhSMEEqXwB-BiISFxyeJx7Dg5LlELSFv1sEuvkeMdt15lY2M7SJz46_U2Sw-cZqT53tPovaJ4D3QFQNsvu257t1sxCrBiICS09YviAoRoSsaoeJl3KqBs8u118SbGA6XAGy4vir9rsvVKY3mjvLfTPbnB9OD2xLhAbocD6kQ2Tqtk3USuYrLHZV3vlU_2N5LkSKeOGBTZYpo96R7UdI_xSX9nY2bLryrinqzn5P6JvR_t4hnfFq-MGiO-O8_L4uf11a77Xm5uv_3o1ptScwqpBKkHBlQ3yPTAGWOgW64GOlSVEo3RDQVjADVvhJKtQiMkM42pBEMzcGmqy-Lz4uuD-zVjTP3RRo3jqCZ0c-yB5hgprZs6ox__Qw9uDlP-rm-By5rS9gSxBdLBxRjQ9D7kcMKf7NSfKumfKulPlfTnSrLo09lZRa1GE9SkbXxWMsHruqZt5j4snEXE57OQEgSX1SNTIZWI</recordid><startdate>201201</startdate><enddate>201201</enddate><creator>WU, Chih-Jen</creator><creator>TSAI, Wen-Hsiang</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Computational geometry</topic><topic>Position (location)</topic><topic>Signal processing</topic><topic>space mapping</topic><topic>table adaptation</topic><topic>Tables (data)</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>WU, Chih-Jen</creatorcontrib><creatorcontrib>TSAI, Wen-Hsiang</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</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>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on circuits and systems for video technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WU, Chih-Jen</au><au>TSAI, Wen-Hsiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Space-Mapping Method for Object Location Estimation Adaptive to Camera Setup Changes for Vision-Based Automation Applications</atitle><jtitle>IEEE transactions on circuits and systems for video technology</jtitle><stitle>TCSVT</stitle><date>2012-01</date><risdate>2012</risdate><volume>22</volume><issue>1</issue><spage>157</spage><epage>162</epage><pages>157-162</pages><issn>1051-8215</issn><eissn>1558-2205</eissn><coden>ITCTEM</coden><abstract>A new space-mapping method for object location estimation, which is adaptive to camera setup changes, for use in various automation applications is proposed. 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| identifier | ISSN: 1051-8215 |
| ispartof | IEEE transactions on circuits and systems for video technology, 2012-01, Vol.22 (1), p.157-162 |
| issn | 1051-8215 1558-2205 |
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| subjects | Applied sciences Artificial intelligence Automation Calibration Camera setup changes Cameras Computer science control theory systems Estimation Exact sciences and technology Floors Image processing Information, signal and communications theory Interpolation Lenses Mapping Mathematical analysis Mobile robots object location estimation Optical imaging Pattern recognition Pattern recognition. Digital image processing. Computational geometry Position (location) Signal processing space mapping table adaptation Tables (data) Telecommunications and information theory |
| title | A Space-Mapping Method for Object Location Estimation Adaptive to Camera Setup Changes for Vision-Based Automation Applications |
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