By the same authors

From the same journal

Multi-view surface reconstruction using polarization

Research output: Contribution to journalArticlepeer-review

Standard

Multi-view surface reconstruction using polarization. / Atkinson, G A ; Hancock, E R .

In: TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS, 2005, p. 309-316.

Research output: Contribution to journalArticlepeer-review

Harvard

Atkinson, GA & Hancock, ER 2005, 'Multi-view surface reconstruction using polarization', TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS, pp. 309-316.

APA

Atkinson, G. A., & Hancock, E. R. (2005). Multi-view surface reconstruction using polarization. TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS, 309-316.

Vancouver

Atkinson GA, Hancock ER. Multi-view surface reconstruction using polarization. TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS. 2005;309-316.

Author

Atkinson, G A ; Hancock, E R . / Multi-view surface reconstruction using polarization. In: TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS. 2005 ; pp. 309-316.

Bibtex - Download

@article{cc9d8e52378946b58105161322e0b6ec,
title = "Multi-view surface reconstruction using polarization",
abstract = "A new technique for surface reconstruction is developed that uses polarization information from two views. One common problem arising from many multiple view techniques is that of finding correspondences between pixels on each image. In the new method, these correspondences are found by exploiting the spontaneous polarization of light caused by reflection to recover surface normals. These normals are then used to recover surface height. The similarity between reconstructed surface regions determines whether or not a pair of points correspond to each other The technique is thus able to overcome the convex/concave ambiguity found in many single view techniques. Because the technique relies on smooth surface regions to detect correspondences, rather than feature detection, it is applicable to objects normally inaccessible to stereo vision. Also due to this fact, it is possible to remove noise without causing over smoothing problems.",
keywords = "IMAGES, SHAPE",
author = "Atkinson, {G A} and Hancock, {E R}",
year = "2005",
language = "English",
pages = "309--316",
journal = "TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS",
issn = "1550-5499",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Multi-view surface reconstruction using polarization

AU - Atkinson, G A

AU - Hancock, E R

PY - 2005

Y1 - 2005

N2 - A new technique for surface reconstruction is developed that uses polarization information from two views. One common problem arising from many multiple view techniques is that of finding correspondences between pixels on each image. In the new method, these correspondences are found by exploiting the spontaneous polarization of light caused by reflection to recover surface normals. These normals are then used to recover surface height. The similarity between reconstructed surface regions determines whether or not a pair of points correspond to each other The technique is thus able to overcome the convex/concave ambiguity found in many single view techniques. Because the technique relies on smooth surface regions to detect correspondences, rather than feature detection, it is applicable to objects normally inaccessible to stereo vision. Also due to this fact, it is possible to remove noise without causing over smoothing problems.

AB - A new technique for surface reconstruction is developed that uses polarization information from two views. One common problem arising from many multiple view techniques is that of finding correspondences between pixels on each image. In the new method, these correspondences are found by exploiting the spontaneous polarization of light caused by reflection to recover surface normals. These normals are then used to recover surface height. The similarity between reconstructed surface regions determines whether or not a pair of points correspond to each other The technique is thus able to overcome the convex/concave ambiguity found in many single view techniques. Because the technique relies on smooth surface regions to detect correspondences, rather than feature detection, it is applicable to objects normally inaccessible to stereo vision. Also due to this fact, it is possible to remove noise without causing over smoothing problems.

KW - IMAGES

KW - SHAPE

M3 - Article

SP - 309

EP - 316

JO - TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS

JF - TENTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1 AND 2, PROCEEDINGS

SN - 1550-5499

ER -