This paper presents a method for computing the visual hull that is based on two novel representations: the rim mesh, which describes the connectivity of contour generators on the object surface; and the visual hull mesh, which describes the exact structure of the surface of the solid formed by intersecting a finite number of visual cones. We describe the topological features of these meshes and show how they can be identified in the image using epipolar constraints. These constraints are used to derive an image-based practical reconstruction algorithm that works with weakly calibrated cameras. Experiments on synthetic and real data validate the proposed approach. 1
Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic m...
Abstract. We present a method for recovering the epipolar geometry from im-ages of smooth surfaces. ...
This paper describes a technique used to approximate the surface of an object’s visual hull. The hul...
International audienceThis paper presents a method for computing the visual hull that is based on tw...
National audienceWe propose an exact method for efficiently and robustly computing the visual hull o...
Article dans revue scientifique avec comité de lecture.Recognizing 3D objects from their 2D silhouet...
Abstract: The marching cubes algorithm has been widely adopted for extracting a surface mesh from a ...
International audienceThis paper addresses the problem of computing visual hulls from image contours...
The visual hull is a geometric entity that relates the shape of an object to its silhouettes or shad...
The marching cubes algorithm has been widely adopted for extracting a surface mesh from a volumetric...
Industrial automation tasks typically require a 3D model of the object for robotic manipulation. The...
Abstract This article presents a novel method for acquiring high-quality solid models of complex 3D ...
[[abstract]]In this paper, we propose a novel contour-based algorithm for 3D object reconstruction f...
Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic m...
Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic m...
Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic m...
Abstract. We present a method for recovering the epipolar geometry from im-ages of smooth surfaces. ...
This paper describes a technique used to approximate the surface of an object’s visual hull. The hul...
International audienceThis paper presents a method for computing the visual hull that is based on tw...
National audienceWe propose an exact method for efficiently and robustly computing the visual hull o...
Article dans revue scientifique avec comité de lecture.Recognizing 3D objects from their 2D silhouet...
Abstract: The marching cubes algorithm has been widely adopted for extracting a surface mesh from a ...
International audienceThis paper addresses the problem of computing visual hulls from image contours...
The visual hull is a geometric entity that relates the shape of an object to its silhouettes or shad...
The marching cubes algorithm has been widely adopted for extracting a surface mesh from a volumetric...
Industrial automation tasks typically require a 3D model of the object for robotic manipulation. The...
Abstract This article presents a novel method for acquiring high-quality solid models of complex 3D ...
[[abstract]]In this paper, we propose a novel contour-based algorithm for 3D object reconstruction f...
Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic m...
Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic m...
Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic m...
Abstract. We present a method for recovering the epipolar geometry from im-ages of smooth surfaces. ...
This paper describes a technique used to approximate the surface of an object’s visual hull. The hul...