Real-Time Non-Rigid Surface Detection

We present a real-time method for detecting deformable surfaces, with no need whatsoever for a priori pose knowledge. Our method starts from a set of wide baseline point matches between an undeformed image of the object and the image in which it is to be detected. The matches are used not only to detect but also to compute a precise mapping from one to the other. The algorithm is robust to large deformations, lighting changes, motion blur, and occlusions. It runs at 10 frames per second on a 2.8 GHz PC and we are not aware of any other published technique that produces similar results. Combining deformable meshes with a well designed robust estimator is key to dealing with the large number of parameters involved in modeling deformable surfaces and rejecting erroneous matches for error rates of up to 95%, which is considerably more than what is required in practice

Real-Time Non-Rigid Surface Detection

On-line diagnostics of power system components is an important area since it allows the diagnostics to be performed at regular intervals during the normal operation of the components. This combined with reliability centered maintenance could lead to reduced customer outages. In this thesis the on-line diagnostic methods for medium voltage cross-linked polyethylene (XLPE) cables are investigated based on Time Domain Reflectometry (TDR). Degradation of XLPE insulated power cables by water-trees (WT) is a primary cause of failure of these cables. The detection of WT and information about the severity of the degradation can be obtained with off-line measurements using dielectric spectroscopy.  In many situations only a limited part of the cable may be degraded by the WT. In such a situation a method for localization of this WT section would be desirable. The developed high frequency measurements superimposed on HV system is presented. It was used to measure the propagation constant of the WT aged cables as a function of the applied HV. This was done in order to study the diagnostic criteria, which could be used for on-line TDR diagnostics of WT aged cables. A physically based dielectric model of WT was developed in order to explain qualitatively and quantitatively the permittivity and loss of WT at different frequencies and voltages. The sensors applicable for the on-line TDR were investigated in terms of sensitivity and bandwidth. High frequency models were built and the simulation results in frequency and time domains were verified by measurements. The developed on-line TDR systems are presented. Their applicability to detect water penetration under the cable sheath and localize the broken screen wires was investigated during the measurements in laboratory environment. The results of field measurements with on-line TDR are presented. Variations due to load cycling of the cable were observed, where an increase in the cable temperature cause an increase of the pulse propagation velocity in the cable. The temperature dependent wave propagation in the cable is investigated and explained by modeling.QC 20100709</p

Registration and analysis of multispectral images acquired during uterine transplantation surgery

Organ transplant success is dependent on blood supply health. A multispectral imaging laparoscope has been used to monitor tissue oxygenation changes during a rabbit uterine transplant. A feature tracking algorithm was used to compensate for movement. © OSA 2012

Deformation-based Augmented Reality for Hepatic Surgery

International audienceIn this paper we introduce a method for augmenting the laparoscopic view during hepatic tumor resection. Using augmented reality techniques, vessels, tumors and cutting planes computed from pre-operative data can be overlaid onto the laparoscopic video. Compared to current techniques, which are limited to a rigid registration of the pre-operative liver anatomy with the intra-operative image, we propose a real-time, physics-based, non-rigid registration. The main strength of our approach is that the deformable model can also be used to regularize the data extracted from the computer vision algorithms. We show preliminary results on a video sequence which clearly highlights the interest of using physics-based model for elastic registration

Tracking and Retexturing Cloth for RealTime Virtual Clothing Applications

Abstract. In this paper, we describe a dynamic texture overlay method from monocular images for real-time visualization of garments in a virtual mirror environment. Similar to looking into a mirror when trying on clothes, we create the same impression but for virtually textured garments. The mirror is replaced by a large display that shows the mirrored image of a camera capturing e.g. the upper body part of a person. By estimating the elastic deformations of the cloth from a single camera in the 2D image plane and recovering the illumination of the textured surface of a shirt in real time, an arbitrary virtual texture can be realistically augmented onto the moving garment such that the person seems to wear the virtual clothing. The result is a combination of the real video and the new augmented model yielding a realistic impression of the virtual piece of cloth

Closed-Form Solution to Non-rigid 3D Surface Registration

We present a closed-form solution to the problem of recovering the 3D shape of a non-rigid inelastic surface from 3D-to-2D correspondences. This lets us detect and reconstruct such a, surface by matching individual images against a reference configuration, which is in contrast to all existing approaches that require initial shape estimates and track deformations from image to image

Surface Deformation Models for Non-Rigid 3--D Shape Recovery

3--D detection and shape recovery of a non-rigid surface from video sequences require deformation models to effectively take advantage of potentially noisy image data. Here we introduce an approach to creating such models for deformable 3--D surfaces. We exploit the fact that the shape of an inextensible triangulated mesh can be parameterized in terms of a small subset of the angles between its facets. We use this set of angles to create a representative set of potential shapes, which we feed to a simple dimensionality reduction technique to produce low-dimensional 3--D deformation models. We show that these models can be used to accurately model a wide range of deforming 3--D surfaces from video sequences acquired under realistic conditions

An efficient unified approach to direct image registration of rigid and deformable surfaces

Image-based deformations are generally used to align images of deformable objecys moving in the 3D space. For the registration of deformable objects, this assumption has shown to give good results. However it is not satisfying for the registration of images of 3D rigid objects as the underlying structure cannot be directly estimated. The general belief is that obtaining the 3D structure directly is difficult. In this article, we propose a parameterization that is well adapted either to align deformable objects or to recover the structure of 3D objects. Furthermore, the formulation leads to an efficient implementation that can considerably reduce the computational load. Experiments with simulated and real data validate the approach for deformable object registration and 3D structure estimation. The computational efficiency is also compared to standard method

New editing techniques for video post-processing

This thesis contributes to capturing 3D cloth shape, editing cloth texture and altering object shape and motion in multi-camera and monocular video recordings. We propose a technique to capture cloth shape from a 3D scene flow by determining optical flow in several camera views. Together with a silhouette matching constraint we can track and reconstruct cloth surfaces in long video sequences. In the area of garment motion capture, we present a system to reconstruct time-coherent triangle meshes from multi-view video recordings. Texture mapping of the acquired triangle meshes is used to replace the recorded texture with new cloth patterns. We extend this work to the more challenging single camera view case. Extracting texture deformation and shading effects simultaneously enables us to achieve texture replacement effects for garments in monocular video recordings. Finally, we propose a system for the keyframe editing of video objects. A color-based segmentation algorithm together with automatic video inpainting for filling in missing background texture allows us to edit the shape and motion of 2D video objects. We present examples for altering object trajectories, applying non-rigid deformation and simulating camera motion.In dieser Dissertation stellen wir Beiträge zur 3D-Rekonstruktion von Stoffoberfächen, zum Editieren von Stofftexturen und zum Editieren von Form und Bewegung von Videoobjekten in Multikamera- und Einkamera-Aufnahmen vor. Wir beschreiben eine Methode für die 3D-Rekonstruktion von Stoffoberflächen, die auf der Bestimmung des optischen Fluß in mehreren Kameraansichten basiert. In Kombination mit einem Abgleich der Objektsilhouetten im Video und in der Rekonstruktion erhalten wir Rekonstruktionsergebnisse für längere Videosequenzen. Für die Rekonstruktion von Kleidungsstücken beschreiben wir ein System, das zeitlich kohärente Dreiecksnetze aus Multikamera-Aufnahmen rekonstruiert. Mittels Texturemapping der erhaltenen Dreiecksnetze wird die Stofftextur in der Aufnahme mit neuen Texturen ersetzt. Wir setzen diese Arbeit fort, indem wir den anspruchsvolleren Fall mit nur einer einzelnen Videokamera betrachten. Um realistische Resultate beim Ersetzen der Textur zu erzielen, werden sowohl Texturdeformationen durch zugrundeliegende Deformation der Oberfläche als auch Beleuchtungseffekte berücksichtigt. Im letzten Teil der Dissertation stellen wir ein System zum Editieren von Videoobjekten mittels Keyframes vor. Dies wird durch eine Kombination eines farbbasierten Segmentierungsalgorithmus mit automatischem Auffüllen des Hintergrunds erreicht, wodurch Form und Bewegung von 2D-Videoobjekten editiert werden können. Wir zeigen Beispiele für editierte Objekttrajektorien, beliebige Deformationen und simulierte Kamerabewegung