An experimental comparison of range image segmentation algorithms
A methodology for evaluating range image segmentation algorithms is proposed. This methodology involves (1) a common set of 40 laser range finder images and 40 structured light scanner images that have manually specified ground truth and (2) a set of defined performance metrics for instances of corr...
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| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence 1996-07, Vol.18 (7), p.673-689 |
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| container_end_page | 689 |
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| container_title | IEEE transactions on pattern analysis and machine intelligence |
| container_volume | 18 |
| creator | Hoover, A. Jean-Baptiste, G. Jiang, X. Flynn, P.J. Bunke, H. Goldgof, D.B. Bowyer, K. Eggert, D.W. Fitzgibbon, A. Fisher, R.B. |
| description | A methodology for evaluating range image segmentation algorithms is proposed. This methodology involves (1) a common set of 40 laser range finder images and 40 structured light scanner images that have manually specified ground truth and (2) a set of defined performance metrics for instances of correctly segmented, missed, and noise regions, over- and under-segmentation, and accuracy of the recovered geometry. A tool is used to objectively compare a machine generated segmentation against the specified ground truth. Four research groups have contributed to evaluate their own algorithm for segmenting a range image into planar patches. |
| doi_str_mv | 10.1109/34.506791 |
| format | Article |
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Four research groups have contributed to evaluate their own algorithm for segmenting a range image into planar patches.</description><subject>Artificial intelligence</subject><subject>Computer vision</subject><subject>Geometrical optics</subject><subject>Geometry</subject><subject>Image segmentation</subject><subject>Laser noise</subject><subject>Measurement standards</subject><subject>Pixel</subject><subject>Shape</subject><subject>Testing</subject><issn>0162-8828</issn><issn>1939-3539</issn><issn>2160-9292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1996</creationdate><recordtype>article</recordtype><recordid>eNqF0D1PwzAQBmALgUQpDKxMmZAYUnyxHcdjVfElVWKB2XKSczFK4mCnEvx7DKlYWe6Ge3Snewm5BLoCoOqW8ZWgpVRwRBagmMqZYOqYLCiURV5VRXVKzmJ8pxS4oGxB1ushw88Rg-txmEyXNb4fTXDRD5m3WTDDDjPXm1Qj7n7N5NLMdDsf3PTWx3NyYk0X8eLQl-T1_u5l85hvnx-eNutt3jBaTTlIVMJiyWtpoQIojOIFYFEjF4AtxapVJTZGKlFa24KqQTaScmaAsZoztiTX894x-I89xkn3LjbYdWZAv4-6qARIKsT_sEyvp9sJ3sywCT7GgFaPKQYTvjRQ_ZOmZlzPaSZ7NVuHiH_uMPwG1b1u7A</recordid><startdate>19960701</startdate><enddate>19960701</enddate><creator>Hoover, A.</creator><creator>Jean-Baptiste, G.</creator><creator>Jiang, X.</creator><creator>Flynn, P.J.</creator><creator>Bunke, H.</creator><creator>Goldgof, D.B.</creator><creator>Bowyer, K.</creator><creator>Eggert, D.W.</creator><creator>Fitzgibbon, A.</creator><creator>Fisher, R.B.</creator><general>IEEE</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19960701</creationdate><title>An experimental comparison of range image segmentation algorithms</title><author>Hoover, A. ; Jean-Baptiste, G. ; Jiang, X. ; Flynn, P.J. ; Bunke, H. ; Goldgof, D.B. ; Bowyer, K. ; Eggert, D.W. ; Fitzgibbon, A. ; Fisher, R.B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c308t-17e95fe64b7f18112a9421e2be451ed0e8d96eca7956ffd19b17c7043a133b433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Artificial intelligence</topic><topic>Computer vision</topic><topic>Geometrical optics</topic><topic>Geometry</topic><topic>Image segmentation</topic><topic>Laser noise</topic><topic>Measurement standards</topic><topic>Pixel</topic><topic>Shape</topic><topic>Testing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hoover, A.</creatorcontrib><creatorcontrib>Jean-Baptiste, G.</creatorcontrib><creatorcontrib>Jiang, X.</creatorcontrib><creatorcontrib>Flynn, P.J.</creatorcontrib><creatorcontrib>Bunke, H.</creatorcontrib><creatorcontrib>Goldgof, D.B.</creatorcontrib><creatorcontrib>Bowyer, K.</creatorcontrib><creatorcontrib>Eggert, D.W.</creatorcontrib><creatorcontrib>Fitzgibbon, A.</creatorcontrib><creatorcontrib>Fisher, R.B.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems 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><jtitle>IEEE transactions on pattern analysis and machine intelligence</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hoover, A.</au><au>Jean-Baptiste, G.</au><au>Jiang, X.</au><au>Flynn, P.J.</au><au>Bunke, H.</au><au>Goldgof, D.B.</au><au>Bowyer, K.</au><au>Eggert, D.W.</au><au>Fitzgibbon, A.</au><au>Fisher, R.B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An experimental comparison of range image segmentation algorithms</atitle><jtitle>IEEE transactions on pattern analysis and machine intelligence</jtitle><stitle>TPAMI</stitle><date>1996-07-01</date><risdate>1996</risdate><volume>18</volume><issue>7</issue><spage>673</spage><epage>689</epage><pages>673-689</pages><issn>0162-8828</issn><eissn>1939-3539</eissn><eissn>2160-9292</eissn><coden>ITPIDJ</coden><abstract>A methodology for evaluating range image segmentation algorithms is proposed. 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| identifier | ISSN: 0162-8828 |
| ispartof | IEEE transactions on pattern analysis and machine intelligence, 1996-07, Vol.18 (7), p.673-689 |
| issn | 0162-8828 1939-3539 2160-9292 |
| language | eng |
| recordid | cdi_ieee_primary_506791 |
| source | IEEE/IET Electronic Library (IEL) |
| subjects | Artificial intelligence Computer vision Geometrical optics Geometry Image segmentation Laser noise Measurement standards Pixel Shape Testing |
| title | An experimental comparison of range image segmentation algorithms |
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