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.

This paper analyses the reconstruction of a 3D scene from multiple images. The proposed approach uses a voxel representation for initializing an implicit radial basis function (RBF) model of the 3D scene. The voxel representation is produced by the space carving algorithm. Disparity errors are identified as inconsistencies between the 3D patches of the scene surface and their pixel block correspondents in the images. A matching algorithm is used for estimating the disparity errors after aligning all these pixel block regions along epipolar lines, each corresponding to a 3D patch of scene surface. An algorithm is derived for updating the RBF center locations using the disparity errors. Experiments are performed on two different sets of images and numerical results are provided when comparing the resulting 3D scene with the ground truth given by a laser scanner.

In this paper we present a new approach for modelling multiple object scenes using images taken from various viewpoints. The voxel representation produced by the space carving is used for estimating the parameters of radial basis function functions (RBFs). A new methodology is proposed for correcting the modelling errors within the RBF framework, by enforcing consistency with the input images by matching along epipolar lines, and enforcing silhouette constraints using the visual hull. The proposed methodology is applied on two datasets consisting of several objects while providing quantitative and qualitative assessment.

This paper considers the problem of modelling a 3-D scene from calibrated images taken from multiple viewpoints. The initial 3-D information is acquired using probabilistic space carving which provides a voxel representation consistent with the given set of images. The scene is afterwards modelled as an implicit surface using radial basis functions (RBF). The mixture of multiorder basis functions models a smoothed 3-D scene representation while providing compactness. We use correspondences between pairs of image patches in order to update the RBF centres for improving the 3-D scene representation. The RBF centre updating leads to improving the consistency between the 3-D model and the given set of images. The proposed method is applied on a complex 3-D scene displaying various objects. 1