Polar snakes: a fast and robust parametric active contour model

We present in this paper a way to perform a fast and robust image segmentation and to track a contour along a sequence of images. Our approach is based on a dynamic deformable model. More precisely, we revisit the physics basedmodel proposed in [1] to show the benefit of using a polar description to model the contour, in particular to cope with the well-known initialization problem. Indeed, we show that this way to proceed leads to diagonal and constant matrices in the equations of the snake evolution yielding therefore to a faster algorithm. Experimental results on image segmentation and contour tracking validate the efficiency of this new formulation. Index Terms — Active contour model, polar description, segmentation, contour tracking. 1

Positioning a camera with respect to planar objects of unknown shape by coupling 2D visual servoing and 3D estimations

International audienceThis paper proposes a way to achieve positioning tasks by 2d visual servoing, when the desired image of the observed object cannot be precisely described. The object is assumed to be planar and motionless but no knowledge about its shape or pose is required. First, we treat the case of a threadlike object and then we show how our approach can be generalized to an object with three particular points. The control law is based on the use of 2d visual servoing and on an estimation of two 3d parameters. We show that this control scheme is not sensitive to the calibration of the camera. We conclude this paper by experimental results relative to objects of unknown shape. In addition, an algorithm to estimate the depth between the object and the camera is provided which finally leads a 3d estimation of the object shape

Une approche contour pour la commande basée image sur objets de forme complexe

International audienceWe describe a method to achieve robotic positioning tasks by image-based visual servoing when the object being observed has a complex and unknown shape. We first focus on the computation of an analytical expression of the interaction matrix according to a polar description of the image contour of the object. Experimental results are presented to validate the proposed algorithm. In particular, the robustness of the control law is tested with respect to a coarse calibrated system, to an approximation of the depth of the object, and to partial occlusion.Nous décrivons une méthode permettant de réaliser des tâches robotiques de positionnement par asservissement visuel basé image quand l'objet observé est de forme complexe et inconnue. Dans un premier temps, nous nous focalisons sur le calcul de l'expression analytique de la matrice d'interaction grâce à description polaire du contour de l'objet. Des résultats expérimentaux valident l'algorithme proposé. En particulier, la robustesse de la loi de commande est testée vis-à-vis d'un système grossièrement calibré, d'une approximation sur la profondeur et d'une occlusion partielle

Optimizing plane-to-plane positioning tasks by image-based visual servoing and structured light

This paper considers the problem of positioning an eye-in-hand system so that it gets parallel to a planar object. Our approach to this problem is based on linking to the camera a structured light emitter designed to produce a suitable set of visual features. The aim of using structured light is not only for simplifying the image processing and allowing lowtextured objects to be considered, but also for producing a control scheme with nice properties like decoupling, convergence and adequate camera trajectory. This paper focuses on an imagebased approach that achieves decoupling in all the workspace and for which the global convergence is ensured in perfect conditions. The behavior of the image-based approach is shown to be partially equivalent to a 3D visual servoing scheme but with a better robustness with respect to image noise. Concerning the robustness of the approach against calibration errors, it is demonstrated both analytically and experimentally

Active rough shape estimation of unknown objects

International audienceThis paper presents a method to determine the rough shape of an object. This is a step in the development of a One Click Grasping Tool, a grasping tool of everyday-life objects for an assistant robot dedicated to elderly or disabled. The goal is to determine the quadric that approximates at best the shape of an unknown object using multi-view measurements. Non-linear optimization techniques are considered to achieve this goal. Since multiple views are necessary, an active vision process is considered in order to minimize the uncertainty on the estimated parameters and determine the next best view. Finally, results that show the validity of the approach are presented

A photometric model for specular highlights and lighting changes. Application to feature points tracking

International audienceThis article proposes a local photometric model that compensates for specular highlights and lighting variations due to position and intensity changes. We define clearly on which assumptions it is based, according to widely used reflection models. Moreover, its theoritical validity is studied according to few configurations of the scene geometry (lighting, camera and object relative locations). Next, this model is used to improve the robustness of points tracking in luminance images with respect to specular highlights and lighting changes

Using robust estimation for visual servoing based on dynamic vision

International audienceThe aim of this article is to achieve accurate visual servoing tasks when the shape of the object being observed as well as the final image are unknown. More precisely, we want to control the orientation of the tangent plane at a certain point on the object corresponding to the center of a region of interest and to move this point to the principal point to fulfill a fixation task. To do that, we perform a 3D reconstruction phase during the servoing. It is based on the measurement of the 2D displacement in the region of interest and on the measurement of the camera velocity. Since the 2D displacement depends on the scene, we introduce an unified motion model to deal with planar as well with non-planar objects. Unfortunately, this model is only an approximation. Thus, we propose to use robust estimation techniques and a 3D reconstruction based on discrete approach. Experimental results compare both approaches

A study on local photometric models and their application to robust tracking

International audienceSince modeling reflections in image processing is a difficult task, most com- puter vision algorithms assume that objects are Lambertian and that no lighting change occurs. Some photometric models can partly answer this issue by assuming that the lighting changes are the same at each point of a small window of interest. Through a study based on specular reflection models, we explicit the assumptions on which these models are implicitly based and the situations in which they could fail. This paper proposes two photometric models, which compensate for spec- ular highlights and lighting variations. They assume that photometric changes vary smoothly on the window of interest. Contrary to classical models, the characteristics of the object surface and the lighting changes can vary in the area being observed. First, we study the validity of these models with re- spect to the acquisition setup: relative locations between the light source, the sensor and the object as well as the roughness of the surface. Then, these models are used to improve feature points tracking by simultaneously estimating the photometric and geometric changes. The proposed methods are compared to well-known tracking methods robust to affine photometric changes. Experimental results on specular objects demonstrate the robust- ness of our approaches to specular highlights and lighting changes