Koichiro Deguchi

Optimal motion control for image-based visual servoing by decoupling translation and rotation

Image-based visual servoing interprets image change directly to camera motion, and control the position and pose of a robot mounting a camera to reach the goal, where the camera obtains just the same image as a given goal image. Because its strategy is to simply minimize the differences between the goal image and the currently obtained image, trajectory of the robot motion cannot be estimated beforehand, and sometimes it results in largely inefficient motion. This paper points out that this inefficient motion is caused by interferences of translation and rotation of images. Then, we propose two algorithms to decouple them by using the homography and the epipolar condition held between the goal image and the current image, and to generate the optimal trajectory of the robot motion to reach the goal straightforwardly.

Shape Reconstruction from an Endoscope Image by Shape from Shading Technique for a Point Light Source at the Projection Center

This paper presents a method for reconstructing the 3D shape of an object from its endoscope image based on image shading. The primary problem is that the endoscope has a light source near the object surface. Most of the conventional shape from shading methods assumed that the light source was distant from the object surface and simplified the analysis. To deal with the near light source, we use the configuration of the endoscope that the light source of the endoscope is well approximated by an imaginary point source at the projection center. In addition, we introduce a notion of equal distance contours of the object surface; by propagating the contours using the image shading, we reconstruct the object shape. This is an extension of the Kimmel?Bruckstein algorithm of shape from shading to the endoscope images. Experimental results for real medical endoscope images of the stomach wall show the feasibility of this method and also show its promising availability for morphological analyses of tumors on human inner organs.

Head pose determination from one image using a generic model

We present a new method for determining the pose of a human head from its 2D image. It does not use any artificial markers put on a face. The basic idea is to use a generic model of a human head, which accounts for variation in shape and facial expression. Particularly, a set of 3D curves are used to model the contours of eyes, lips and eyebrows. A technique called iterative closest curve matching (ICC) is proposed, which aims at recovering the pose by iteratively minimizing the distances between the projected model curves and their closest image curves. Because curves contain richer information (such as curvature and length) than points, ICC is both more robust and more efficient than the well-known iterative closest point matching techniques (ICP). Furthermore, the image can be taken by a camera with unknown internal parameters, which can be recovered by our technique thanks to the 3D model. Preliminary experiments show that the proposed technique is promising and that an accurate pose estimate can be obtained from just one image with a generic head model.

Shape reconstruction from an endoscope image by shape-from-shading technique for a point light source at the projection center

Describes an approach to reconstructing a shape from its shaded image in the case where a point light source is at the projection center. This condition well approximates the imaging system of an endoscope. In this case, the image gray level depends on not only the gradient of the object surface but also the distance from the light source to each point on the surface. To deal with this difficulty, the authors introduce the evolution equation for equal-range contours on the surface. Propagating this contour by solving the equation, one can reconstruct a shape. Experimental results far real medical endoscope images of a human stomach inner wall show feasibility of this method, and present a promising technique for morphological analysis of tumors on human inner organs.

Visual servoing using eigenspace method and dynamic calculation of interaction matrices

A general scheme to represent the relation between dynamic images and camera motion is presented, and its application to visual servoing proposed. For a specific object, the camera cannot obtain any arbitrary image, so that the possible combination of the camera pose and the obtained image should be constrained on a lower dimensional hyper surface within the product space of all the combinations. The visual servoing, for example, is interpreted as to find a path on this surface leading to a given goal image. Our approach is to analyse the properties of this surface and utilise its tangential property for visual servoing. We propose to use the principal component analysis and to represent images with a composition of small number of eigen-images by using the Karhunen-Loeve expansion. We describe that a normal vector of this surface is related to the so-called interaction matrix. We then present a dynamic estimation of the normal vectors to move the robot arm mounting a camera to a goal position where a given goal image will be obtained. Experimental results of visual servoing method show the feasibility and applicability of our proposed approach.

Reconstructing shape from shading with a point light source at the projection center: shape reconstruction from an endoscope image

A new method for reconstructing three dimensional object from an endoscope image is presented. The proposed method uses image shading generated by a light source at the endoscope head. In this case, the light source is near to the object surface so that the image brightness depends on not only the surface gradients but also the distance from the light source to the surface point. To deal with this difficulty, we consider the imaging system of the endoscope as the system having a point light source at the projection center. The object surface is reconstructed by propagating equal-distance contours, spatial curves composed of points at an equal distance from the light source. The propagation is controlled by the image shading. We use the level-sets method for numerical computation. Experimental results for real medical images show feasibility of this method.

Shape reconstruction from endoscope image by its shadings

This paper describes a total image processing to reconstruct a shape from endoscope images. We have already developed a shape reconstruction procedure from an endoscope image sequence, and produced a global 3D sketch of object shape from an image sequence taken by a moving endoscope. Here, we propose a method to obtain fine 3D structure from its shading based on the global sketch. We consider the shape from the shading problem in the case where a point light source is at the projection center. This condition well approximates the imaging system of an endoscope. In this case, the image gray level depends on not only the gradient of the object surface but also the distance from the light source to each point on the surface. To deal with this difficulty, we introduce the evolution equation for equal-distance contours on the surface. Propagating this contour by solving the equation, we can reconstruct a shape. Experimental results for real medical endoscope images of a human stomach inner wall show feasibility of this method, and present a promising technique for morphological analysis of tumors on human inner organs.

Simultaneous determination of camera pose and intrinsic parameters by visual servoing

In this paper, we propose a new method for camera calibration that is an extension of the visual servoing technique. The basic objective of visual servoing is to control the camera motion so as to obtain the goal image which is given a priori. In this paper, we consider the case where intrinsic camera parameters are not known. First, we compose the goal image with initial guesses of the parameters. Then, in addition to the control of the camera motion, we dynamically modify the goal image according to the estimated intrinsic camera parameters. When the same image with the modified goal image is obtained, both the true intrinsic and extrinsic camera parameters are determined. We describe this new method with theoretical details and experiments using synthetic and real images.

On the Classification of Singular Points for the Global Shape from Shading Problem: A Study of the Constraints Imposed by Isophotes

This paper concerns with the global surface reconstruction from a shaded image. It is known that the key to the global reconstruction lies in classifying singular points in the image into three categories—convex, concave or saddle classes. Several methods have been proposed for this problem. All of them require explicit solution of the shape from shading equation. Therefore the results may suffer from image noise and modeling errors of the surface reflecting properties and illumination. If the classification of singular points without such an explicit solution of the equation would have been possible, then the global reconstruction could have been made much more precise. The present work aims towards developing a classification technique where such a explicit solution is not required. Our first step is to show that isophotes (lines of equal brightness) provide some information on the types of singulax points; if two isophotes exist which evolve from two singular points and meet each other, then the one of the two singular points is elliptic and the other is hyperbolic. This is derived from intrinsic properties of a smooth (twice differentiable) surface.

Regularized polygonal approximation for analysis and interpretation of planar contour figures

A method for approximating contour figures with piecewise-linear polygons using a criterion function based on regularization theory is presented. In this method, it is possible to select the degree of fineness of the approximation to a given contour figure with a parameter in the criterion function, which represents a tradeoff between the fitness and the simplicity of the polygonal model. However, it is shown that, for a given figure, only a few types of stable models optimize the criterion with a variety of values of the parameter. This means that only a few types of polygons may be suitable approximations for representing the original characteristic features of the figure. This method derives such polygons automatically from the given figures. Thus, the approach shows potential as a powerful method for the analysis and interpretation of planar contour figures.<<ETX>>