Details
| Original language | English |
|---|---|
| Title of host publication | Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit |
| Pages | 704-705 |
| Number of pages | 2 |
| Publication status | Published - 1991 |
| Event | 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Maui, United States Duration: 3 Jun 1991 → 6 Jun 1991 |
Publication series
| Name | Proc 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 subject areas
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Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit. 1991. p. 704-705 (Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
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 -