Shape adaptation for modelling of 3D objects in natural scenes

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

Autoren

  • C. E. Liedtke
  • H. Busch
  • R. Koch

Organisationseinheiten

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksProc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit
Seiten704-705
Seitenumfang2
PublikationsstatusVeröffentlicht - 1991
Veranstaltung1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Maui, USA / Vereinigte Staaten
Dauer: 3 Juni 1991 → 6 Juni 1991

Publikationsreihe

NameProc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit

Abstract

Rigid 3-D objects were modeled automatically from an image sequence taken by a camera that was rotated around the object. The image sequence was recorded using a calibrated camera which allows one to measure the camera positions and to estimate the true object size. The 3-D object shape was obtained in two steps. The object silhouettes were employed to find the enclosing volume of the object. The volume was converted into a flexible surface representation and the 3-D shape was refined based on the texture information of the object surface. Texture mapping was applied to generate a highly realistic 3-D model of the object.

ASJC Scopus Sachgebiete

Zitieren

Shape adaptation for modelling of 3D objects in natural scenes. / Liedtke, C. E.; Busch, H.; Koch, R.
Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit. 1991. S. 704-705 (Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

Liedtke, CE, Busch, H & Koch, R 1991, Shape adaptation for modelling of 3D objects in natural scenes. in Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit. Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit, S. 704-705, 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Maui, Hawaii, USA / Vereinigte Staaten, 3 Juni 1991.
Liedtke, C. E., Busch, H., & Koch, R. (1991). Shape adaptation for modelling of 3D objects in natural scenes. In Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit (S. 704-705). (Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit).
Liedtke CE, Busch H, Koch R. Shape adaptation for modelling of 3D objects in natural scenes. in Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit. 1991. S. 704-705. (Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit).
Liedtke, C. E. ; Busch, H. ; Koch, R. / Shape adaptation for modelling of 3D objects in natural scenes. Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit. 1991. S. 704-705 (Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit).
Download
@inproceedings{1142f60936184373a28de4ff5e67dd16,
title = "Shape adaptation for modelling of 3D objects in natural scenes",
abstract = "Rigid 3-D objects were modeled automatically from an image sequence taken by a camera that was rotated around the object. The image sequence was recorded using a calibrated camera which allows one to measure the camera positions and to estimate the true object size. The 3-D object shape was obtained in two steps. The object silhouettes were employed to find the enclosing volume of the object. The volume was converted into a flexible surface representation and the 3-D shape was refined based on the texture information of the object surface. Texture mapping was applied to generate a highly realistic 3-D model of the object.",
author = "Liedtke, {C. E.} and H. Busch and R. Koch",
year = "1991",
language = "English",
isbn = "0818621486",
series = "Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit",
pages = "704--705",
booktitle = "Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit",
note = "1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition ; Conference date: 03-06-1991 Through 06-06-1991",

}

Download

TY - GEN

T1 - Shape adaptation for modelling of 3D objects in natural scenes

AU - Liedtke, C. E.

AU - Busch, H.

AU - Koch, R.

PY - 1991

Y1 - 1991

N2 - Rigid 3-D objects were modeled automatically from an image sequence taken by a camera that was rotated around the object. The image sequence was recorded using a calibrated camera which allows one to measure the camera positions and to estimate the true object size. The 3-D object shape was obtained in two steps. The object silhouettes were employed to find the enclosing volume of the object. The volume was converted into a flexible surface representation and the 3-D shape was refined based on the texture information of the object surface. Texture mapping was applied to generate a highly realistic 3-D model of the object.

AB - Rigid 3-D objects were modeled automatically from an image sequence taken by a camera that was rotated around the object. The image sequence was recorded using a calibrated camera which allows one to measure the camera positions and to estimate the true object size. The 3-D object shape was obtained in two steps. The object silhouettes were employed to find the enclosing volume of the object. The volume was converted into a flexible surface representation and the 3-D shape was refined based on the texture information of the object surface. Texture mapping was applied to generate a highly realistic 3-D model of the object.

UR - http://www.scopus.com/inward/record.url?scp=0026400161&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0026400161

SN - 0818621486

T3 - Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit

SP - 704

EP - 705

BT - Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit

T2 - 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Y2 - 3 June 1991 through 6 June 1991

ER -