Silhouette and stereo fusion for 3D object modeling

Signal and Image Processing Department, CNRS UMR 5141, Ecole Nationale Supérieure des Télécommunications, France
Computer Vision and Image Understanding (Impact Factor: 1.54). 01/2003; 96(3):367-392. DOI: 10.1016/j.cviu.2004.03.016
Source: DBLP


In this paper, we present a new approach to high quality 3D object reconstruction. Starting from a calibrated sequence of color images, the algorithm is able to reconstruct both the 3D geometry and the texture. The core of the method is based on a deformable model, which defines the framework where texture and silhouette information can be fused. This is achieved by defining two external forces based on the images: a texture driven force and a silhouette driven force. The texture force is computed in two steps: a multi-stereo correlation voting approach and a gradient vector flow diffusion. Due to the high resolution of the voting approach, a multi-grid version of the gradient vector flow has been developed. Concerning the silhouette force, a new formulation of the silhouette constraint is derived. It provides a robust way to integrate the silhouettes in the evolution algorithm. As a consequence, we are able to recover the contour generators of the model at the end of the iteration process. Finally, a texture map is computed from the original images for the reconstructed 3D model.

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    • "This is a functional that penalizes solutions that do not respect prior assumptions, and plays a key role both in the quality of the reconstruction, as well as in the efficiency of the numerical optimization scheme. The most principled approaches to 3-d reconstruction aim to infer a collection of (multiply-connected, piecewise smooth) surfaces directly, represented intrinsically without regards to the images [2] [10] [18] [28] [38] [21] [42], as evident by the large body of literature on shape space and shape optimization. In these methods, both the geometry and the topology is then inferred to fit the available images. "
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 01/2015
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    • "In shape-from-silhouettes, a set of silhouettes extracted from images is used to model the 3D scene by generating the convex hull produced by a union of projection cones [1] [2]. An energy function used both texture and silhouettes for guiding a deformable model in [10] for single 3D object representation. The methodology described in this paper aims to robustly enforce the consistency of scenes with multiple objects with their corresponding contours segmented from images. "
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    ABSTRACT: This paper proposes enforcing the consistency with segmented contours when modelling scenes with multiple objects from multi-view images. A certain rough initialization of the 3D scene is assumed to be available and in the case of multiple objects inconsistencies are expected. In the proposed shape-from-contours approach images are segmented and back-projections of segmented contours are used for enforcing the consistency of the segmented contours with 3D objects from the scene. We provide a study for the physical requirements for detecting occlusions when reconstructing 3-D scenes with multiple objects.
    IEEE International Conference on Image Processing, Paris, France; 10/2014
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    • "De plus, la surface est une 2-variété, c'est à dire une liste de triangles dans l'espace tels que tout point de la surface a un voisinage homéomorphe à un disque. Cette propriété est nécéssaire pour définir la normale et la courbure de la surface [4], et est donc utilisée par de nombreux algorithmes comme le raffinement de surface impliquant une régularisation (lissage [8], stéréo dense [9], . . . ) et d'autres [4] [11]. La plupart des méthodes éparses sont basées sur la sculpture dans une triangulation de Delaunay 3D. "
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