We present a new post-processing step to enhance the resolution of range images. Using one or two registered and potentially high-resolution color images as reference, we iteratively refine the input low-resolution range image, in terms of both its spatial resolution and depth precision. Evaluation using the Middlebury benchmark shows across-the-board improvement for sub-pixel accuracy. We also demonstrated its effectiveness for spatial resolution enhancement up to 100 × with a single reference image. 1.

Translucent objects pose a difficult problem for traditional structured light 3D scanning techniques. Subsurface scattering corrupts the range estimation in two ways: by drastically reducing the signal-to-noise ratio and by shifting the intensity peak beneath the surface to a point which does not coincide with the point of incidence. In this paper we analyze and compare two descattering methods in order to obtain reliable 3D coordinates for translucent objects. By using polarization-difference imaging, subsurface scattering can be filtered out because multiple scattering randomizes the polarization direction of light while the surface reflectance partially keeps the polarization direction of the illumination. The descattered reflectance can be used for reliable 3D reconstruction using traditional optical 3D scanning techniques, such as structured light. Phase-shifting is another effective descattering technique if the frequency of the projected pattern is sufficiently high. We demonstrate the performance of these two techniques and the combination of them on scanning real-world translucent objects. 1.

Abstract. We propose a new method named compressive structured light for recovering inhomogeneous participating media. Whereas conventional structured light methods emit coded light patterns onto the surface of an opaque object to establish correspondence for triangulation, compressive structured light projects patterns into a volume of participating medium to produce images which are integral measurements of the volume density along the line of sight. For a typical participating medium encountered in the real world, the integral nature of the acquired images enables the use of compressive sensing techniques that can recover the entire volume density from only a few measurements. This makes the acquisition process more efficient and enables reconstruction of dynamic volumetric phenomena. Moreover, our method requires the projection of multiplexed coded illumination, which has the added advantage of increasing the signal-to-noise ratio of the acquisition. Finally, we propose an iterative algorithm to correct for the attenuation of the participating medium during the reconstruction process. We show the effectiveness of our method with simulations as well as experiments on the volumetric recovery of multiple translucent layers, 3D point clouds etched in glass, and the dynamic process of milk drops dissolving in water. 1

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Figure 1: Active refocusing of images. (a) Image acquired by projecting a sparse set of illumination dots on the scene. (b) The dots are automatically removed from the acquired image, and the defocus of the dots and a color segmentation of the image are used to compute an approximate depth map of the scene with sharp boundaries. (c and d) The depth map and the dot-removed image are used to smoothly refocus the scene. (e) The refocusing can also be done for an image taken immediately before or after but illuminated as desired. We present a system for refocusing images and videos of dynamic scenes using a novel, single-view depth estimation method. Our method for obtaining depth is based on the defocus of a sparse set of dots projected onto the scene. In contrast to other active illumination techniques, the projected pattern of dots can be removed from each captured image and its brightness easily controlled in order to avoid under- or over-exposure. The depths corresponding to the projected dots and a color segmentation of the image are used to compute an approximate depth map of the scene with clean region boundaries. The depth map is used to refocus the acquired image after the dots are removed, simulating realistic depth of field effects. Experiments on a wide variety of scenes, including close-ups and live action, demonstrate the effectiveness of our method. CR Categories: I.3.7 [Computer Graphics]: Three-Dimensional

We present algorithms for plane-based calibration of general radially distorted cameras. By this we understand cameras that have a distortion center and an optical axis such that the projection rays of pixels lying on a circle centered on the distortion center, form a right viewing cone centered on the optical axis. The camera is said to have a single viewpoint (SVP) if all such viewing cones have the same apex (the optical center), otherwise we speak of NSVP cases. This model encompasses the classical radial distortion model [4], fisheyes and most central or non-central catadioptric cameras. Calibration consists in the estimation of the distortion center, the opening angles of all viewing cones and their optical centers. We present two approaches of computing a full calibration from dense correspondences of a single or multiple planes with known Euclidean structure. The first one is based on a geometric constraint linking viewing cones and their intersections with the calibration plane (conic sections). The second approach is an homography-based method. Experiments using simulated and a broad variety of real cameras show great stability. Furthermore, we provide a comparison with Hartley-Kang’s algorithm [14], which however can not handle such a broad variety of camera configurations, showing similar performance.

In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory.

We present a simple and high-quality 3D scanning system based on structured light. It uses the common setup of a video projector, a computer-controlled turntable and a single camera. Geometry is acquired using a combination of Gray code and phase-shift projections, and it is stored and processed in a point-based representation. We achieve

Abstract — The registration of full 3-D models is an important task in computer vision. Range finders only let to reconstruct a partial view of the object. The last years, many authors have proposed several techniques to register 3D surfaces from multiple views in which there are basically two aspects to consider. First, poor registration in which some sort of correspondences are established. Second, accurate registration in order to obtain a better solution. In this paper, a survey of the most common techniques is presented and includes experimental results of some of them. I.

3D documentation and visualization of Cultural Heritage objects is an expanding application area. The selection of the right technology for these kinds of applications is very important and strictly related to the project requirements, budget and user’s experience. Active sensors, i.e. triangulation based laser scanners and structured light systems are used for many kinds of 3D object reconstruction tasks and in particular for 3D documentation of cultural heritage objects. This study presents some experiences in the results of two case studies in which a close-range structured light system is used for the 3D digitization. The paper includes all necessary steps of the 3D object modeling pipeline from data acquisition to 3D visualization.