We propose a new application of stochastic point-based rendering, which was recently proposed for implicit surfaces, to large-scale laser-scanned 3D point data. Specifically, we propose a scheme to apply the rendering to transparent and fused visualization of recent large and complex laser-scanned data from cultural assets. Our scheme uses 3D points that are directly acquired using a laser scanner as the rendering primitives. For laser-scanned data that consist of more than 107 or 108 3D points, the pre-processing stage takes only a few minutes, and the rendering stage is executable at interactive frame rates. We do not encounter rendering artifacts originating from the indefiniteness of depth-sorted orders of rendering primitives. Fused visualization with various visual assistants is also possible. We demonstrate the effectiveness of our scheme by visualizing a campus building and a culturally important festival float.

We propose a novel approach to haptic interact with complex inhomogeneous elastic objects like organs. In surgery simulations, representation of complex inhomogeneous elastic objects which have various physical properties and geometries is required. Also, consideration of geometric nonlinearity is required. At present, in order to simulate such objects correctly, we have to use the nonlinear FEM model with high resolution meshes. Furthermore, higher update rate (about from several hundred [Hz]) is required for stable force feedback. Therefore, computational cost becomes problem. In this paper, to solve this problem, we propose an adaptive and embedded deformation model. This approach uses both an online re-mesh deformation model and a corotational FEM model together. Our approach can update an inverse of a global stiffness matrix of a corotational FEM model quickly during the online remeshing (tetrahedron subdivision/simplification). In addition, an efficient computation algorithm by GPU is also proposed. We implemented this approach into our prototype surgery simulation system, and then we performed evaluation experiments to verify the feasibility and effectiveness of our approach.

This work obtains shaking-free route panoramas from a vehicle borne camera. We detect the shaking and waving profile of the camera and rectify a long route panorama automatically for an ideal parallel-perspective projection. Different from the traditional flow based approach that works on entire frame by point tracking, we create a stationary blurred temporal image called condensed slice during the scene scanning. This image yields long and visible traces from distinct and distant features and horizontal features as the evidences of camera motion, and it diminishes other features irrelevant to the motion as well. We track traces in the condensed slice and rectify the route panorama at the sub-pixel level without shape analysis in video frames. The significance of the approach is in its effectiveness visually confirmable in the results, global rectification as the vehicle moves forward, and efficiency for real-time processing using the minimum data set.

We developed a two-shot 6-band image capturing system consisting of a large-format camera, a customized interference filter, and a scanning digital back to capture a 185-M-pixel images. The interference filter is set in front of the camera lens to obtain a 6-band image, that is, two 3-band images, one taken with the filter and the other without it. After correction of optical aberrations caused by the interference filter as well as system arrangement errors, the two images are combined into a 6-band image. The 6-band image was converted into a color-managed RGB image embedded ICC profile. In experiments, object images were captured as several divided parts and synthesized as almost 500-M-pixel image by using an image stitching technique. Resolution of the captured images is 0.02 mm/pixel. This paper discusses the camera system with its focus on some early modern tapestries used in the Kyoto Gion Festival. After the experiments, we interviewed a craftsman to assess the image's importance in archiving and analyzing fabric structures.

Frictional information is important for manipulating and representing real behavior of objects in a virtual space via haptic devices. In this paper we propose an active and automatic extraction method of friction properties based on Haptic Vision; we estimate the parameters of friction models such as LuGre model, Coulomb model, Dhal model, by analyzing observed shape and force data obtained by Haptic Vision and then evaluate the performance of each friction model.

On a moving vehicle, speedy motion extraction from video is demanded. Different from the traditional motion estimation methods that track or match 2D features in consecutive motion-blurred images, this work explores a novel approach to find motion without explicit shape analysis. We take spatial integration of intensities in each frame and the obtained consecutive profiles provide distinct motion traces in a visual form. The camera motion can be followed in the integrated images briefly, rather than from complex feature extraction and iterative computation. The resulting motion parameters are used for normalizing length and removing shaking of route panoramas. The results are robust and the method is particularly efficient for real time processing.

The subjects described in this paper are a realtime adaptive modeling method for deformable objects and an adaptive cutting method for 3D surface meshes. In the literature so far, adaptive models with high resolution representations at regions of high deformation have not been investigated. In this paper we propose a new method for real-time modeling of soft objects, of which high resolutions dynamically adapt to the regions of high deformation. In order to reduce the computational cost in comparison with the previous methods we use the bisection refinement algorithm. The experimental results show the effectiveness of the proposed method. The cutting operation of 3D surface meshes plays an important role in surgery simulators. One of the important requirements for surgical simulators is the visual reality. We propose a new strategy for cutting on surface mesh: refinement and separate strategy consisting of the refinement followed by the separation of the refined mesh element. Since the advantage of the low computational cost, the bisection refinement method is utilized for the refinement process. The proposed strategy gives the faithful representation of the interaction path

In this paper, we propose a novel approach to extracting rheological properties of deformable objects based on Haptic vision, which was proposed for vision-based automatic construction of virtual environment simulators. The method consists of two parts: 1) the "touch and see" part to cause deformation behavior by exerting known contact force on the object using a robot hand, and then observe how the deformed shape return to the original after contact force is removed, using a range sensor and a force-feedback sensor mounted on the robot hand, 2) the analysis and parameter extraction part from the acquired range images and force-feedback data. Experimental results using springs and wheat dough demonstrated the validity and effectiveness of the proposed approach to viscoelastic parameter extraction of rheological objects.

Real-world objects exhibit rich physical interaction behaviours on contact. Such behaviours depend on how heavy and hard it is when held, how its surface feels when touched, how it deforms on contact, etc. Recently, there are thus growing needs for haptic exploration to estimate and extract such physical object properties as mass, friction, elasticity, relational constraints etc.. In this paper, we propose a novel paradigm, we call haptic vision,which is a vision-based haptic exploration approach toward an automatic construction of reality-based virtual space simulator, by augmenting active vision with active touch. We apply this technique to mass, relational constraints estimation and elasticity, and use these results to construct virtual object manipulation simulator. Experimental results show that feasibility and validity of the proposed approach.

We propose a general-purpose parallel algorithm for image segmentation, which doesn't require any prior knowledge about the image or region. The algorithm, which is based on our adaptive mesh generation scheme, provides a binary tree structured split-and-merge mechanism to search and localize boundaries along discontinuities, and adapts the partition of the image to those detected discontinuities. This algorithm is independent of the order of processing or starting point, which be an important issue with parallel algorithms. Even though overlapping by only one pixel wide boundary between process blocks, by adopting the smoothness-based local features as homogeneity criteria, consistencies are maintained without the overhead of communication between adjacent process blocks. Our efficient hierarchical stepwise mechanism in merging target evaluation makes the merge process so simple and efficient that only two brother blocks are considered at each merge step in binary fashion.

Automatic acquisition of a three-dimensional object model is one of major goals of computer vision research. We develop a new algorithm for reconstructing the 3D shapes of objects from multiview images which are automatically acquired based on the symmetry in stable poses. Our approach is based on a "shape from function" strategy. That is, shape is inferred by observing and estimating "the stability in stable poses", which is the most fundamental condition for objects to be functioning in the real world. Based on that assumption, we first observe the object from the vertical top and estimate a plane of symmetry using the center of gravity and the symmetrical axis of the silhouette in the top view image. We then estimate the next viewpoints, from which the estimated symmetry are examined with silhouettes obtained as projections on the estimated plane of symmetry. By executing this symmetry estimation-examination process recursively, we reconstruct the 3D shape of the object as a product of straight homogeneous generalized cylinders (SHGCs) whose cross section and the axis direction are constrained from the silhouette at each view-point and the viewing direction respectively by using octree representation or a CAD system. Experimental results show that the effectiveness of the approach in reconstructing the 3D shape of object.

In this paper, we present a correlation-based face recognition approach based on the analysis of maximum and minimum principal curvatures and their directions. We treat face recognition problem as a 3D shape recognition problem of free-form curved surfaces. Our approach is based on a 3D vector sets correlation method which does not require either face feature extraction or surface segmentation. Each face in both input images and the model database, is represented as an extended Gaussian image (EGI), constructed by mapping principal curvatures and their directions at each surface points, onto two unit spheres, each of which represents ridge and valley lines respectively. Individual face is then recognized by evaluating the similarities among others by using Fisher's spherical correlation on EGIs of faces. The method is tested for its simplicity and robustness and successively implemented for each of the face range images for NRCC (National Research Council of Canada) 3D image data files. Results shows that shape information from surface curvatures provides vital clues in distinguishing and identifying such fine surface structure as human faces.

The authors seek to reconstruct a polyhedral representation of surfaces from range data that can adapt to the intrinsic surface shape and that might be used as an accurate CAD model. An adaptive mesh model for hierarchical triangulation of 3-D objects is presented. An adaptive mesh generation algorithm is developed that recursively bisects mesh elements by increasing the number of mesh nodes according to surface curvatures. The recursive subdivision based on such a viewpoint-invariant feature yields the hierarchical surface triangulation that is intrinsic to the surface, and satisfies the absolute accuracy criterion. In order to avoid cracks that often occur during adaptive subdivision, an algorithm is developed that collects subdivision information by recursively expanding the region of reference until a sudden surface change is observed. Computation results on real range data of human faces are shown.>

A homotopy describes the transformation of one arbitrary curve into another that shares the same endpoints. In this paper, we propose a deformable cylinder model, based on homotopy, in which an arbitrary surface interpolated between two contours via a blending function is transformed into another surface over time. We then show how this homotopic deformation can be applied to the realistic animation of human faces in a virtual space teleconferencing system. Specifically, we show that facial expressions such as wrinkling of the forehead and opening and closing of the mouth can be synthesized and animated in real time through 3D homotopic deformations.

The straight homogeneous generalized cylinder (SHGC) comprises a class of objects for which recovery of pose and shape from image is generally an underconstrained problem. It is shown that for a major subclass of SHGCs, namely, the right straight homogeneous generalized cylinders, the 3-D pose (tilt and slant) and shape (cross section and scaling function) can be completely determined if the cross sections are symmetrical. From the mutual orthogonality of the cylinder axis, the symmetry axis and transverse axis of the cross section, their slants can be determined from their tilts, the 2-D orientations of their projections onto the image. The 2-D cylinder axis and skewed symmetry axis of the cross sections are extracted by using the property that tangents to the image curves at corresponding points meet on the axes. Once the pose is recovered, the cross section and scaling function of the object can also be determined from the cross section contour and extremal contours, respectively.>

Surface reconstruction and visualization from sparse and incomplete surface data is a fundamental problem and has received growing attention in both computer vision and graphics. The paper introduces a novel approach to recovering and visualizing complex shapes from range data, in which a surface of unknown shape is reconstructed with view-invariant characteristics on arbitrary viewplanes from sparsely sampled surface range data so that the entire surface can be visualized from any view points with constant. The authors develop a graphical reconstruction model based on differential geometry using adaptive and arbitrarily oriented meshes, in which the number of surface nodes is generated dynamically on an active viewing plane and then increased in number and influence one another until the entire surface has been interpolated with a sufficient accuracy. The computation results on real range data of human faces are shown.>

A computational scheme is presented for obtaining a characteristic description of a free-form curved surface from 3-D range images whose natural modes are in the form of level (equidistance) contours. The novelty in this scheme is that dense surface contours are used to directly estimate the surface curvatures in a systematic fashion without having to explicitly or implicitly compute any partial derivatives. The principle of the scheme is described, and the framework of computational paradigm is outlined for a shape description (shape from level contours) of the free-form curved object from its local surface properties. The objective is to obtain an invariant viewpoint and stable representation that is useful in 3-D object reconstruction and recognition. Although the scheme is based on analysis of level contours, the computation model for shape representation is general and applicable to any dense range image.>

A representation scheme is presented for shapes of three-dimensional curved objects whose surface curvatures are not continuous at all points, i.e., surfaces with C/sup 1/ continuity only. A class of surface curves and points called surface structure descriptors for this representation are defined. These descriptors consist of subsets of lines of curvature and their intersections and are based on local descriptions of smooth surfaces. The surface structure curves are derived from the zero-crossings, asymptotes and gradient directions of the Gaussian and mean curvatures of the surface. A smooth surface sketch in terms of the geometrical structures of enclosing boundaries of bumps and dents, ridge and valley lines, and peaks and pits is developed. A hierarchical description of curved surfaces that leads to a global shape representation of the object is obtained from these descriptors. To handle the discontinuities of surface curvatures, a computational scheme is introduced in which gradient directions of surface curvatures at the discontinuities can be inferred. Simulation results on the computation of these descriptors from curved surfaces are shown. Potential applications of these representation schemes in computer vision tasks are discussed.>

The authors consider the 3-D shape representation problem for a class of range image where the natural model of the acquired range data is in the form of level set contours (equidistance contours), as exemplified by a moire interferometry range system. They present a novel surface curvature computation scheme that directly computes the surface curvatures (the principal curvatures, Gaussian curvature, and mean curvature) from the equidistance contours without any explicit computations or implicit estimates of partial derivatives. They show how the special nature of the equidistance contours, specifically. the dense information of the surface curves in the 2-D contour plane, turns into an advantage for the computation of the surface curvatures. The approach is based on using simple geometric construction to obtain the surface normals, the normal sections, and the normal curvatures. This method is general and can be extended to any dense range image data. Computation results on both real and synthesized equidistance range contours are shown.>