Rigid, affine and locally affine registration of free-form surfaces

In this paper, we propose a new framework to perform f nonrigid surface registration. It is based on various extensions of an iterative algorithm recently presented by several researchers (Besl, Zhang, Chen, Menq, Champleboux) to f rigidly register surfaces represented by a set of 3D points, when a prior estimate of the displacement is available. Our framework consists of three stages: First, we search for the best f rigid displacement to superpose the two surfaces. We show how to efficiently use curvatures to superpose principal frames at possible corresponding points in order to find a prior rough estimate of the displacement and initialize the iterative algorithm. Second, we search for the best f affine transformation. We introduce differential information in points coordinates: this allows us to match locally similar points. Then, we show how principal frames and curvatures are transformed by an affine transformation. Finally, we introduce this differential information in a global criterion minimized by extended Kalman filtering. Third, we locally deform the surface. Instead of computing a global affine transformation, we attach to each point a f local affine transformation varying smoothly along the surface. We call this deformation a locally affine deformation. All these stages are illustrated with experiments on various real biomedical surfaces (teeth, faces, skulls, brains and hearts), which demonstrate the validity of the approach

Rigid, Affine and Locally Affine Registration of Free-Form Surfaces

International audienceIn this paper, we propose a new framework to perform nonrigid surface registration. It is based on various extensions of an iterative algorithm recently presented by several researchers (Besl and McKay, 1992; Champleboux et al., 1992; Chen and Medioni, 1992; Menq and Lai, 1992; Zhang, 1994) to rigidly register surfaces represented by a set of 3D points, when a prior estimate of the displacement is available. Our framework consists of three stages: - First, we search for the best rigid displacement to superpose the two surfaces. We show how to efficiently use curvatures to superpose principal frames at possible corresponding points in order to find a prior rough estimate of the displacement and initialize the iterative algorithm. - Second, we search for the best affine transformation. We introduce differential information in points coordinates: this allows us to match locally similar points. Then, we show how principal frames and curvatures are transformed by an affine transformation. Finally, we introduce this differential information in a global criterion minimized by extended Kalman filtering in order to ensure the convergence of the algorithm. - Third, we locally deform the surface. Instead of computing a global affine transformation, we attach to each point a local affine transformation varying smoothly along the surface. We call this deformation a locally affine deformation. All these stages are illustrated with experiments on various real biomedical surfaces (teeth, faces, skulls, brains and hearts), which demonstrate the validity of the approach

3D-2D projective registration of free-form curves and surfaces

International audienceSome medical interventions require knowing the correspondence between an MRI/CT image and the actual position of the patient. Examples occur in neurosurgery and radiotherapy, but also in video surgery (laparoscopy). We present in this paper three new techniques for performing this task without artificial markers. To do this, we find the 3D-2D projective transformation (composition of a rigid displacement and a perspective projection) which maps a 3D object onto a 2D image of this object. Depending on the object model (curve or surface), and on the 2D image acquisition system (X-Ray, video), the techniques are different but the framework is common: Results are presented on a variety of real medical data to demonstrate the validity of our approach

Definition of a 4D Continuous Polar Transformation for the Tracking and the Analysis of LV Motion

Cardiologists assume that analysis of the motion of the heart (especially the left ventricle) can give precise information about the health of the myocardium. A 4D polar transformation is defined to describe the left ventricle (LV) motion and a method is presented to estimate it from sequences of 3D images. The transformation is defined in 3D-planispheric coordinates by a small number of parameters involved in a set of simple linear equations. It is continuous and regular in time and space, periodicity in time can be imposed. The local motion can be easily decomposed into a few canonical motions (centripetal contraction, rotation around the long-axis, elevation). To recover the motion from original data, the 4D polar transformation is calculated using an adaptation of the Iterative Closest Point algorithm. We present the mathematical framework and a demonstration of its feasability on a set of synthetic but realistic datapoints, simulating the motion of the LV and on a gated SPECT sequence

Comparison between two predicting methods of labial coarticulation

International audienceThe construction of a highly intelligible talking head involving relevant lip gestures is especially important for hearing impaired people. This requires realistic rendering of lip and jaw movements and thus relevant modeling of lip coarticulation. This paper presents the comparison between the Cohen & Massaro prediction algorithm and our concatenation plus completion strategy guided by phonetic knowledge. Although results show that Cohen & Massaro perform slightly better, the concatenation and completion strategy approximates consonant clusters markedly better particularly for the protrusion parameter. These results also show the concatenation and completion strategy could be easily improved via the recording of better reference models for isolated vowels

3D-2D projective registration of free-form curves and surfaces

Some medical interventions require knowing the correspondence between an MRI/CT image and the actual position of the patient. Examples occur in neurosurgery and radiotherapy, but also in video surgery (laparoscopy). We present in this paper three new techniques for performing this task without artificial markers. To do this, we find the \bf 3D-2D projective transformation (composition of a rigid displacement and a perspective projection) which maps a 3D object onto a 2D image of this object. Depending on the object model (curve or surface), and on the 2D image acquisition system (X-Ray, video), the techniques are different but \bf the framework is common: \beginitemize \item We first find an estimate of the transformation using bitangent lines or bitangent planes. These are first order semi-differential invariants \citeMundy. \item Then, introducing the normal or tangent, we define a distance between the 3D object and the 2D image, and we minimize it using extensions of the Iterative Closest Point algorithm (\citeBesl,Zhang). \item We deal with the critical problem of outliers by computing Mahalanobis distances and performing generalized $\chi^2$ tests. \enditemize Results are presented on a variety of real medical data to demonstrate the validity of our approach

Definition of a 4D continuous polar transformation for the tracking and the analysis of LV motion

International audienceA 4D polar transformation is defined to describe the left ventricle (LV) motion and a method is presented to estimate it from sequences of 3D images. The transformation is defined in 3D-planispheric coordinates by a small number of parameters involved in a set of simple linear equations. It is continuous and regular in time and space, periodicity in time can be imposed. The local motion can be easily decomposed into a few canonical motions (centripetal contraction, rotation around the long-axis, elevation). To recover the motion from original data, the 4D polar transformation is calculated using an adaptation of the Iterative Closest Point algorithm. We present the mathematical framework and a demonstration of its feasability on a gated SPECT sequence

Transcribing Southern Min Speech Corpora with a Web-Based Language Learning System

International audienceThe paper proposes a human-computation-based scheme for transcribing Southern Min speech corpora. The core idea is to implement a Web-based language learning system to collect orthographic and phonetic labels from a large amount of language learners and choose the commonly input labels as the transcriptions of the corpora. It is essentially a technology of distributed knowledge acquisition. Some computeraided mechanisms are also used to verify the collected transcriptions. The benefit of the scheme is that it makes the transcribing task neither tedious nor costly. No significant budget should be made for transcribing large corpora. The design of a system for transcribing Min Nan speech corpora is described in detail. The application of a prototype version of the system shows that this transcribing scheme is an effective and economical wa

Building and Testing a Statistical Shape Model of the Human Ear Canal

Abstract. Today the design of custom in-the-ear hearing aids is based on personal experience and skills and not on a systematic description of the variation of the shape of the ear canal. In this paper it is described how a dense surface point distribution model of the human ear canal is built based on a training set of laser scanned ear impressions and a sparse set of anatomical landmarks placed by an expert. The landmarks are used to warp a template mesh onto all shapes in the training set. Using the vertices from the warped meshes, a 3D point distribution model is made. The model is used for testing for gender related differences in size and shape of the ear canal.