Stereo and controlled movement
Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplyi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yuille, Alan [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
1990 |
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| Schlagwörter: |
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| Anmerkung: |
© Kluwer Academic Publishers 1990 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of computer vision - Kluwer Academic Publishers, 1987, 4(1990), 2 vom: März, Seite 141-152 |
|---|---|
| Übergeordnetes Werk: |
volume:4 ; year:1990 ; number:2 ; month:03 ; pages:141-152 |
| Links: |
|---|
| DOI / URN: |
10.1007/BF00127814 |
|---|
| Katalog-ID: |
OLC2057732738 |
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| 520 | |a Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. | ||
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10.1007/BF00127814 doi (DE-627)OLC2057732738 (DE-He213)BF00127814-p DE-627 ger DE-627 rakwb eng 004 VZ Yuille, Alan verfasserin aut Stereo and controlled movement 1990 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1990 Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. Probability Distribution Image Processing Artificial Intelligence Computer Vision Traditional Method Geiger, Davi aut Enthalten in International journal of computer vision Kluwer Academic Publishers, 1987 4(1990), 2 vom: März, Seite 141-152 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:4 year:1990 number:2 month:03 pages:141-152 https://doi.org/10.1007/BF00127814 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2012 GBV_ILN_2190 GBV_ILN_2244 GBV_ILN_2409 GBV_ILN_4046 GBV_ILN_4307 GBV_ILN_4700 AR 4 1990 2 03 141-152 |
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10.1007/BF00127814 doi (DE-627)OLC2057732738 (DE-He213)BF00127814-p DE-627 ger DE-627 rakwb eng 004 VZ Yuille, Alan verfasserin aut Stereo and controlled movement 1990 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1990 Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. Probability Distribution Image Processing Artificial Intelligence Computer Vision Traditional Method Geiger, Davi aut Enthalten in International journal of computer vision Kluwer Academic Publishers, 1987 4(1990), 2 vom: März, Seite 141-152 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:4 year:1990 number:2 month:03 pages:141-152 https://doi.org/10.1007/BF00127814 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2012 GBV_ILN_2190 GBV_ILN_2244 GBV_ILN_2409 GBV_ILN_4046 GBV_ILN_4307 GBV_ILN_4700 AR 4 1990 2 03 141-152 |
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10.1007/BF00127814 doi (DE-627)OLC2057732738 (DE-He213)BF00127814-p DE-627 ger DE-627 rakwb eng 004 VZ Yuille, Alan verfasserin aut Stereo and controlled movement 1990 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1990 Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. Probability Distribution Image Processing Artificial Intelligence Computer Vision Traditional Method Geiger, Davi aut Enthalten in International journal of computer vision Kluwer Academic Publishers, 1987 4(1990), 2 vom: März, Seite 141-152 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:4 year:1990 number:2 month:03 pages:141-152 https://doi.org/10.1007/BF00127814 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2012 GBV_ILN_2190 GBV_ILN_2244 GBV_ILN_2409 GBV_ILN_4046 GBV_ILN_4307 GBV_ILN_4700 AR 4 1990 2 03 141-152 |
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10.1007/BF00127814 doi (DE-627)OLC2057732738 (DE-He213)BF00127814-p DE-627 ger DE-627 rakwb eng 004 VZ Yuille, Alan verfasserin aut Stereo and controlled movement 1990 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1990 Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. Probability Distribution Image Processing Artificial Intelligence Computer Vision Traditional Method Geiger, Davi aut Enthalten in International journal of computer vision Kluwer Academic Publishers, 1987 4(1990), 2 vom: März, Seite 141-152 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:4 year:1990 number:2 month:03 pages:141-152 https://doi.org/10.1007/BF00127814 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2012 GBV_ILN_2190 GBV_ILN_2244 GBV_ILN_2409 GBV_ILN_4046 GBV_ILN_4307 GBV_ILN_4700 AR 4 1990 2 03 141-152 |
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10.1007/BF00127814 doi (DE-627)OLC2057732738 (DE-He213)BF00127814-p DE-627 ger DE-627 rakwb eng 004 VZ Yuille, Alan verfasserin aut Stereo and controlled movement 1990 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1990 Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. Probability Distribution Image Processing Artificial Intelligence Computer Vision Traditional Method Geiger, Davi aut Enthalten in International journal of computer vision Kluwer Academic Publishers, 1987 4(1990), 2 vom: März, Seite 141-152 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:4 year:1990 number:2 month:03 pages:141-152 https://doi.org/10.1007/BF00127814 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2012 GBV_ILN_2190 GBV_ILN_2244 GBV_ILN_2409 GBV_ILN_4046 GBV_ILN_4307 GBV_ILN_4700 AR 4 1990 2 03 141-152 |
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Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. © Kluwer Academic Publishers 1990 |
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Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. © Kluwer Academic Publishers 1990 |
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Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithm in detail for the cases of head and eye rotation and illustrate it with some examples. © Kluwer Academic Publishers 1990 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2057732738</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504072015.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s1990 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/BF00127814</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2057732738</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)BF00127814-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Yuille, Alan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Stereo and controlled movement</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">1990</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Kluwer Academic Publishers 1990</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We describe a method to solve the stereo correspondence using controlled head (or camera) movements. These movements, which can be due to eye rotation, head rotation, or head translation, essentially supply additional imageframes which can be used to constrain the stereo matching by supplying monocular cues. Because the movements are small, traditional methods of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first (based on the monocular cues), thereby reducing the ambiguity for the remaining matches. 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