A new algorithm for computing the projection matrix between a LIDAR and a camera based on line correspondences
In this paper, we present a new algorithm to directly calculate the projection matrix between a camera and a LIDAR. Since Line correspondences are used to construct the geometric constraint in our algorithm, the calibration target is flexible and any object with straight line boundary can be an appr...
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creator | Lipu Zhou Zhidong Deng |
description | In this paper, we present a new algorithm to directly calculate the projection matrix between a camera and a LIDAR. Since Line correspondences are used to construct the geometric constraint in our algorithm, the calibration target is flexible and any object with straight line boundary can be an appropriate calibration target. The algorithm has two stages. Firstly, the linear solution is estimated by minimizing the algebraic error. Then it is refined by optimizing the geometric error. Two different kinds of geometric distance are discussed and the one using the distance from a laser point to the plane, which is formed by back-projecting from an image line, is chosen. Because the quality of the measurements impacts on the accuracy of the final result, a sampling strategy is also given to obtain high quality measurements and avoid overfitting. Simulation and experimental results validate the proposed algorithm and sampling strategy. |
doi_str_mv | 10.1109/ICUMT.2012.6459706 |
format | Conference Proceeding |
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Since Line correspondences are used to construct the geometric constraint in our algorithm, the calibration target is flexible and any object with straight line boundary can be an appropriate calibration target. The algorithm has two stages. Firstly, the linear solution is estimated by minimizing the algebraic error. Then it is refined by optimizing the geometric error. Two different kinds of geometric distance are discussed and the one using the distance from a laser point to the plane, which is formed by back-projecting from an image line, is chosen. Because the quality of the measurements impacts on the accuracy of the final result, a sampling strategy is also given to obtain high quality measurements and avoid overfitting. 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Since Line correspondences are used to construct the geometric constraint in our algorithm, the calibration target is flexible and any object with straight line boundary can be an appropriate calibration target. The algorithm has two stages. Firstly, the linear solution is estimated by minimizing the algebraic error. Then it is refined by optimizing the geometric error. Two different kinds of geometric distance are discussed and the one using the distance from a laser point to the plane, which is formed by back-projecting from an image line, is chosen. Because the quality of the measurements impacts on the accuracy of the final result, a sampling strategy is also given to obtain high quality measurements and avoid overfitting. Simulation and experimental results validate the proposed algorithm and sampling strategy.</description><subject>Calibration</subject><subject>Cameras</subject><subject>Equations</subject><subject>Laser radar</subject><subject>Lasers</subject><subject>Linear programming</subject><subject>Mathematical model</subject><issn>2157-0221</issn><issn>2157-023X</issn><isbn>1467320161</isbn><isbn>9781467320160</isbn><isbn>9781467320177</isbn><isbn>9781467320153</isbn><isbn>1467320153</isbn><isbn>146732017X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9kNtKw0AQhtcTWGtfQG_2BVJ39phclnoqVASp4F3ZJLPtlmYTNivVtzdg9WqG-X4-mJ-QG2BTAFbcLebvL6spZ8CnWqrCMH1CJoXJQWojhrMxp2TEQZmMcfFxRq7-gIbzf8Dhkkz6fsfY4Mk1L-SIhBkNeKB2v2mjT9uGujbSqm26z-TDhqYt0i62O6ySbwNtbIr-i5aYDoiBWrpc3M_eqA31sFe2wWhpaXus6RDe-4CDKkbsuzbUGCrsr8mFs_seJ8c5JqvHh9X8OVu-Pi3ms2XmwaiUSciNRFYLh9zKXAjjSq0BjTOlqw0vHdfglORKSy2lcqVkwBivkA1fKTEmt79aj4jrLvrGxu_1sTnxA2N_XZY</recordid><startdate>201210</startdate><enddate>201210</enddate><creator>Lipu Zhou</creator><creator>Zhidong Deng</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201210</creationdate><title>A new algorithm for computing the projection matrix between a LIDAR and a camera based on line correspondences</title><author>Lipu Zhou ; Zhidong Deng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-41874e0d3fe2a48337fb661e7f7bfd72bf261f5425646445fb401002ce029453</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Calibration</topic><topic>Cameras</topic><topic>Equations</topic><topic>Laser radar</topic><topic>Lasers</topic><topic>Linear programming</topic><topic>Mathematical model</topic><toplevel>online_resources</toplevel><creatorcontrib>Lipu Zhou</creatorcontrib><creatorcontrib>Zhidong Deng</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>Lipu Zhou</au><au>Zhidong Deng</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A new algorithm for computing the projection matrix between a LIDAR and a camera based on line correspondences</atitle><btitle>2012 IV International Congress on Ultra Modern Telecommunications and Control Systems</btitle><stitle>ICUMT</stitle><date>2012-10</date><risdate>2012</risdate><spage>436</spage><epage>441</epage><pages>436-441</pages><issn>2157-0221</issn><eissn>2157-023X</eissn><isbn>1467320161</isbn><isbn>9781467320160</isbn><eisbn>9781467320177</eisbn><eisbn>9781467320153</eisbn><eisbn>1467320153</eisbn><eisbn>146732017X</eisbn><abstract>In this paper, we present a new algorithm to directly calculate the projection matrix between a camera and a LIDAR. Since Line correspondences are used to construct the geometric constraint in our algorithm, the calibration target is flexible and any object with straight line boundary can be an appropriate calibration target. The algorithm has two stages. Firstly, the linear solution is estimated by minimizing the algebraic error. Then it is refined by optimizing the geometric error. Two different kinds of geometric distance are discussed and the one using the distance from a laser point to the plane, which is formed by back-projecting from an image line, is chosen. Because the quality of the measurements impacts on the accuracy of the final result, a sampling strategy is also given to obtain high quality measurements and avoid overfitting. Simulation and experimental results validate the proposed algorithm and sampling strategy.</abstract><pub>IEEE</pub><doi>10.1109/ICUMT.2012.6459706</doi><tpages>6</tpages></addata></record> |
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ispartof | 2012 IV International Congress on Ultra Modern Telecommunications and Control Systems, 2012, p.436-441 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Calibration Cameras Equations Laser radar Lasers Linear programming Mathematical model |
title | A new algorithm for computing the projection matrix between a LIDAR and a camera based on line correspondences |
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