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By adopting different reconstruction techniques, 3D sensors generate different point clouds of various scales for the same object. This paper presents a new algorithm to align point clouds of different scales. First, shape descriptors based on different neighboring sizes are calculated on each point. Secondly, for each neighboring size, principle components analysis is applied on all descriptors to...
Telerobotic manipulation allows patients living with upper limb impairments to interact with a variety of environments and accomplish through teleoperation daily activities such as playing, feeding, self-care, and leisure, that would otherwise be difficult to perform. In this paper, we propose a nonlinear mapping between the patient's range of motion and the workspace of an environment being manipulated...
We present an algorithm to compute parametric models of dense foliage. The guiding principles of our work are automatic reconstruction and compact artist friendly representation. We use Bezier patches to model leaf surface, which we compute from images and point clouds of dense foliage. We present an algorithm to segment individual leaves from colour and depth data. We then reconstruct the Bezier...
Cardiac function assessment is a critical step in cardiology and 3D ultrasound plays an increasingly important role. Automatic left ventricular (LV) segmentation remains however challenging particularly in the presence of artifacts and for images with low contrast-to-noise ratio (CNR). It is thus crucial to give segmentation tools prior information on the LV shape in order to fill in the gaps when...
Pre-learnt subspace methods, e.g., 3DMMs, are significant exploration for the synthesis of 3D faces by assuming that faces are in a linear class. However, the human face is in a nonlinear manifold, and a new test are always not in the pre-learnt subspace accurately because of the disparity brought by ethnicity, age, gender, etc. In the paper, we propose a parametric T-spline morphable model (T-splineMM)...
We propose a new formulation of the active surface model in 3D. Instead of aligning a shape dictionary through the similarity transform, we consider more flexible affine transformations and introduce an alignment method that is unbiased in the sense that it implicitly constructs a common reference shape. Our formulation is expressed in the continuous domain and we provide an algorithm to exactly implement...
Biomedical image segmentation is an active field of research where deformable models have proved to be efficient. The geometric representation of such models determines their ability to approximate the shape of interest as well as the speed of convergence of related optimization algorithms. We present a new tensor-product parameterization of surfaces that offers the possibility of local refinement...
Needles are tools widely used in minimally invasive surgery. During such procedures the localization of the needle and its tip is a challenging situation because of the needle deformations due to its interactions with tissues. To tackle this problem, instrumented needles with sensors have been currently developed to allow needle reconstruction and tip localization. In conventional surgery this difficulty...
This paper presents an original method for aligning 3D shapes modeled as NURBS based B-rep models, exploiting partial symmetries of the shape. Aligning 3D shapes is an important pre-processing step in 3D shape retrieval and indexation: a reliable alignment of the shapes is necessary. Given a 3D model, three canonical planes define the normalized pose. We characterize the first canonical plane by an...
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