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Accurate range image registration: Eliminating or modelling outliers
Automatic and accurate range image registration is often a prerequisite step for range image analysis and interpretation. Due to occlusion, appearance and disappearance of points in different images, outliers inevitably occur. In this case, various techniques to eliminate and model outliers have bee...
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| creator | Yonghuai Liu Honghai Liu Longzhuang Li Baogang Wei |
| description | Automatic and accurate range image registration is often a prerequisite step for range image analysis and interpretation. Due to occlusion, appearance and disappearance of points in different images, outliers inevitably occur. In this case, various techniques to eliminate and model outliers have been proposed for accurate range image registration. The objective of this paper is to experimentally investigate which of the outlier elimination and modelling is more effective for the evaluation of possible correspondences established, so that a deep insight into how advanced range image registration algorithms will be developed can be obtained. The experimental results based on both synthetic data and real images show that the outlier modelling often outperforms the outlier elimination in the sense of producing more accurate and robust range image registration results. |
| doi_str_mv | 10.1109/EFTA.2007.4416933 |
| format | conference_proceeding |
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Due to occlusion, appearance and disappearance of points in different images, outliers inevitably occur. In this case, various techniques to eliminate and model outliers have been proposed for accurate range image registration. The objective of this paper is to experimentally investigate which of the outlier elimination and modelling is more effective for the evaluation of possible correspondences established, so that a deep insight into how advanced range image registration algorithms will be developed can be obtained. 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Due to occlusion, appearance and disappearance of points in different images, outliers inevitably occur. In this case, various techniques to eliminate and model outliers have been proposed for accurate range image registration. The objective of this paper is to experimentally investigate which of the outlier elimination and modelling is more effective for the evaluation of possible correspondences established, so that a deep insight into how advanced range image registration algorithms will be developed can be obtained. The experimental results based on both synthetic data and real images show that the outlier modelling often outperforms the outlier elimination in the sense of producing more accurate and robust range image registration results.</description><subject>Cameras</subject><subject>Computer science</subject><subject>Geometrical optics</subject><subject>Image registration</subject><subject>Iterative algorithms</subject><subject>Iterative closest point algorithm</subject><subject>Laser noise</subject><subject>Motion estimation</subject><subject>Optical imaging</subject><subject>Optical sensors</subject><issn>1946-0740</issn><issn>1946-0759</issn><isbn>9781424408252</isbn><isbn>1424408253</isbn><isbn>9781424408269</isbn><isbn>1424408261</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpVkM1KxEAQhMc_cFnzAOIlL5DYPdOTzHgLa1aFBS_reRmSThjJj0yyB9_eoMuCfejm64KiKCHuEVJEsI_ldl-kEiBPiTCzSl2IyOYGSRKBkZm9FCu0lCWQa3v1T9Py-qwR3Ipomj5hGdKE2q7Ec1FVx-BmjoMbWo5975YduPXTvLz9ODzFZed7PywwtPEY4n6suet-4Th3nsN0J24a100cne5afGzL_eY12b2_vG2KXeIlmjmxaJTTRoJTVW1rstQAIANrnSGSrpqs0VbVRlPucsXKVBIrMo1ix7V0ai0e_nw9Mx--whI2fB9OnagfOedQNA</recordid><startdate>20070101</startdate><enddate>20070101</enddate><creator>Yonghuai Liu</creator><creator>Honghai Liu</creator><creator>Longzhuang Li</creator><creator>Baogang Wei</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20070101</creationdate><title>Accurate range image registration: Eliminating or modelling outliers</title><author>Yonghuai Liu ; Honghai Liu ; Longzhuang Li ; Baogang Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i218t-9183a5820a3cd9d494f001e0e5561145cf6f593d8547a73e38c21c48f3eaed2a3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Cameras</topic><topic>Computer science</topic><topic>Geometrical optics</topic><topic>Image registration</topic><topic>Iterative algorithms</topic><topic>Iterative closest point algorithm</topic><topic>Laser noise</topic><topic>Motion estimation</topic><topic>Optical imaging</topic><topic>Optical sensors</topic><toplevel>online_resources</toplevel><creatorcontrib>Yonghuai Liu</creatorcontrib><creatorcontrib>Honghai Liu</creatorcontrib><creatorcontrib>Longzhuang Li</creatorcontrib><creatorcontrib>Baogang Wei</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 (IEL)</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>Yonghuai Liu</au><au>Honghai Liu</au><au>Longzhuang Li</au><au>Baogang Wei</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Accurate range image registration: Eliminating or modelling outliers</atitle><btitle>2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007)</btitle><stitle>EFTA</stitle><date>2007-01-01</date><risdate>2007</risdate><spage>1316</spage><epage>1323</epage><pages>1316-1323</pages><issn>1946-0740</issn><eissn>1946-0759</eissn><isbn>9781424408252</isbn><isbn>1424408253</isbn><eisbn>9781424408269</eisbn><eisbn>1424408261</eisbn><abstract>Automatic and accurate range image registration is often a prerequisite step for range image analysis and interpretation. Due to occlusion, appearance and disappearance of points in different images, outliers inevitably occur. In this case, various techniques to eliminate and model outliers have been proposed for accurate range image registration. The objective of this paper is to experimentally investigate which of the outlier elimination and modelling is more effective for the evaluation of possible correspondences established, so that a deep insight into how advanced range image registration algorithms will be developed can be obtained. The experimental results based on both synthetic data and real images show that the outlier modelling often outperforms the outlier elimination in the sense of producing more accurate and robust range image registration results.</abstract><pub>IEEE</pub><doi>10.1109/EFTA.2007.4416933</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1946-0740 |
| ispartof | 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007), 2007, p.1316-1323 |
| issn | 1946-0740 1946-0759 |
| language | eng |
| recordid | cdi_ieee_primary_4416933 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cameras Computer science Geometrical optics Image registration Iterative algorithms Iterative closest point algorithm Laser noise Motion estimation Optical imaging Optical sensors |
| title | Accurate range image registration: Eliminating or modelling outliers |
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