ManhattanFusion : Online Dense Reconstruction of Indoor Scenes From Depth Sequences
We present a new framework for online dense 3D reconstruction of indoor scenes by using only depth sequences. This research is particularly useful in cases with a poor light condition or in a nearly featureless indoor environment. The lack of RGB information makes long-range camera pose estimation d...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 28(2022), 7 vom: 10. Juli, Seite 2668-2681
|
|---|
| 1. Verfasser: |
Yazdanpour, Mahdi
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Fan, Guoliang,
Sheng, Weihua |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2022
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics
|
|---|
| Schlagworte: | Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, Non-U.S. Gov't |
|---|