proposé.
est implanté en Matlab sur un Pentium 4 1,86GHz.
A.6
Conclusion
Nous avons proposé une nouvelle approche pour capturer les déformations d’une surface à par- tir de données issues d’un capteur 3D. Le modèle représentant la surface est un maillage régulier, déformé sous différentes contraintes, afin de correspondre parfaitement aux nuages de points 3D. La fonction de coût introduite est composée d’informations a priori, comme par exemple un lissage spatio-temporel des déformations et de termes d’attraction aux données. Les termes d’inextensibilité et d’attraction aux bords apparaissent être cruciaux pour rendre bien posé ce problème naturellement ambigu. La fonction de coût est minimisée par l’algorithme LM-ICP en prenant en compte la nature extrêmement creuse des matrices (Hessienne et Jacobienne) mises en jeu. Les résultats obtenus sont très prometteurs ; les performances de reconstruction sont satisfaisantes sur les cas traités. L’approche proposée est testée sur deux jeux de données issus de capteurs différents, démontrant sa généricité. L’algorithme proposé est en outre relativement rapide est très facile à implanter.
Nous avons appliqué notre approche à la synthèse d’images et de vidéos présentant une surface déformable. D’autres applications peuvent néanmoins être visées, comme la réalité augmentée, no- tamment pour les effets spéciaux, ou bien la compression de données.
En perspective, la sélection automatique des poids associés aux différents termes constituant la fonction de coût devra être étudiée. Nous avons déjà discuté de cette problématique dans la conclusion de ce tapuscrit.
Figure 4: Synthetically interpolated views. Images are generated by linear
interpolation between Figures 2 (a), (b) and (c) respectively.
11
FIG. A.5 – Images synthétisées en interpolant les surfaces reconstruites à partir des données des
−160 −140 −120 −100 −80 −60 −40 −20 −120 −100 −80 −60 −40 −20 0 580 590 600 610 620 630 640 (a) (b)
Figure 5: The cover sequence: intensity image of the cover (a) and the 3D point cloud (b).
(a) (b)
Figure 6: Data extraction: 2D boundary (a) and selected 3D data (b). 3D boundary are highlighted with dark color.
12 (a) −160 −140 −120 −100 −80 −60 −40 −20 −120 −100 −80 −60 −40 −20 0 580 590 600 610 620 630 640 (a) (b)
Figure 5: The cover sequence: intensity image of the cover (a) and the 3D point cloud (b).
(a) (b)
Figure 6: Data extraction: 2D boundary (a) and selected 3D data (b). 3D boundary are highlighted with dark color.
12
(b)
FIG. A.6 – La séquence de la couverture. (a) Image d’intensité représentant la couverture. (b) Le
nuage de points 3D associé.
−160 −100 −80 −60 −40 −20 0 580 590 600 610 620 630 640
(a)
(b)
Figure 5: The cover sequence: intensity image of the cover (a) and the 3D point
cloud (b).
(a)
(b)
Figure 6: Data extraction: 2D boundary (a) and selected 3D data (b). 3D
boundary are highlighted with dark color.
12
(a) −160 −140 −120 −100 −80 −60 −40 −20 −120 −100 −80 −60 −40 −20 0 580 590 600 610 620 630 640 (a) (b)Figure 5: The cover sequence: intensity image of the cover (a) and the 3D point cloud (b).
(a) (b)
Figure 6: Data extraction: 2D boundary (a) and selected 3D data (b). 3D boundary are highlighted with dark color.
12
(b)
FIG. A.7 – Extraction des données d’entrée pour la séquence de la couverture. (a) Les contours 2D. (b) Le nuage de points 3D correspondant uniquement à la région d’intérêt. Les points 3D appar- tenant aux bords de la région d’intérêt sont représentés en noir.
(a1)
(a2)
(b1)
(b2)
(c1)
(c2)
(d1)
(d2)
(e1)
(e2)
(f1)
(f2)
(g1)
(g2)
(h1)
(h2)
(i1)
(i2)
(j1)
(j2)
Figure 7: Cover sequence: 10 selected frames. For each frame the 2D intensity
(·,1) and the 3D data (·,2) is visualized. The grid models are shown in the 3D
space as well as their projection in the 2D image.
14
FIG. A.8 – Résultat du recalage sur la séquence de la couverture. (·1) les images d’intensité sur lesquelles sont surimposées les contours 2D ainsi que la reprojection des modèles estimés. (·2) les nuages de points 3D et les modèles 3D estimés.
Figure 8: Synthesized movie: some selected frames. Each frame of the movie is
projected to the reconstructed model by simulating a deforming video screen.
15
FIG. A.9 – Vidéo de synthèse représentant un film sur un écran déformable. Chaque image consti- tuant le film est projetée sur la surface reconstruite au cours de la séquence de la couverture.
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