Franc Solina

Recovery of parametric models from range images: the case for superquadrics with global deformations

A method for recovery of compact volumetric models for shape representation of single-part objects in computer vision is introduced. The models are superquadrics with parametric deformations (bending, tapering, and cavity deformation). The input for the model recovery is three-dimensional range points. Model recovery is formulated as a least-squares minimization of a cost function for all range points belonging to a single part. During an iterative gradient descent minimization process, all model parameters are adjusted simultaneously, recovery position, orientation, size, and shape of the model, such that most of the given range points lie close to the models surface. A specific solution among several acceptable solutions, where are all minima in the parameter space, can be reached by constraining the search to a part of the parameter space. The many shallow local minima in the parameter space are avoided as a solution by using a stochastic technique during minimization. Results using real range data show that the recovered models are stable and that the recovery procedure is fast. >

Superquadrics for segmenting and modeling range data

We present an approach to reliable and efficient recovery of part-descriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g. in terms of surfaces). The approach is based on the recover-and-select paradigm. We present several experiments on real and synthetic range images, where we demonstrate the stability of the results with respect to viewpoint and noise.

15 seconds of fame

15 seconds of fame is an interactive installation that every 15 seconds generates a new pop-art portrait of a randomly selected viewer. The installation was inspired by Andy Warhols ironical statement that in the future everybody will be famous for 15 minutes. The installation detects human faces and crops them from the wide-angle view of people standing before the installation. Pop-art portraits are then generated by applying randomly selected filters to a randomly chosen face from the audience. These portraits are then shown in 15-second intervals on the flat-panel computer monitor, which is framed as a painting.

A direct recovery of superquadric models in range images using recover-and-select paradigm

We present a novel approach to reliable and efficient recovery of part-descriptions from range images. We show that a set of superquadric models can be directly recovered from unsegmented range data, as opposed to methods which attempt the recovery of volumetric models only after the data has been pre-segmented using extensive pre-processing. The approach is based on the recover-and-select paradigm which consists of two intertwined stages: model-recovery and model-selection. At the model-recovery stage a redundant set of superquadrics is initiated in the image and allowed to grow, which involves an iterative procedure combining data classification and parameter estimation. All the recovered models are passed to the model-selection procedure where only the models resulting in the simplest overall description are selected.

Segmentation versus object representation—are they separable?

When vision is used for moving through the environment, for manipulating or for recognizing objects, it has to simplify the visual input to the level that is required for the specific task. To simplify means to partition images into entities that correspond to individual regions, objects and parts in the real world and to describe those entities only in detail sufficient for performing a required task. For visual discrimination, shape is probably the most important property. After all, line drawings of scenes and objects are usually sufficient for description and subsequent recognition. In computer vision literature this partitioning of images and description of individual parts is called segmentation and shape representation. Segmentation and shape representation appear to be distinct problems and are treated as such in most computer vision systems. In this paper we try to disperse this notion and show that there is no clear division between segmentation and shape representation. Solving any one of those two problems separately is very difficult. On the other hand, if any one of the two problems is solved first, the other one becomes much easier. For example, if the image is correctly divided into parts, the subsequent shape description of those parts gets easier. The opposite is also true when the shapes of parts are known, the partitioning of the image gets simpler.

Part-level object recognition using superquadrics

This paper proposes a technique for object recognition using superquadric built models. Superquadrics, which are three-dimensional models suitable for part-level representation of objects, are reconstructed from range images using the recover-and-select paradigm. Using interpretation trees, the presence of an object from the model database can be hypothesized. These hypotheses are verified by projecting and re-fitting the object model to the range image of the scene which at the same time enables a better localization of the object in the scene.

Theoretical foundations of computer vision

Attentive Visual Motion Processing: Computations in the Log-Polar Plane.- Invariant Thinning and Distance Transform.- Recognition of Images Degraded by Linear Motion Blur without Restoration.- Symmetric Bi- and Trinocular Stereo: Tradeoffs between Theoretical Foundations and Heuristics.- Surface from Motion-without and with Calibration.- Properties of Pyramidal Representations.- A Robust Approach to Estimation of Parametric Models.- Computer Vision and Mathematical Morphology.- A Variational Approach to the Design of Early Vision Algorithms.- Banach Constructor and Image Compression.- Piecewise Linear Approximation of Planar Jordan Curves and Arcs: Theory and Applications.- Segmentation with Volumetric Part Models.- Theoretical Foundations of Anisotropic Diffusion in Image Processing.- Stability and Likelihood of Views of Three Dimensional Objects.

User interface for video observation over the internet

This paper presents the design and application of a system for live video transmission and remote camera control over the World Wide Web. Extensive testing of the Internet Video Server (IVS) prompted us to improve its user interface. The GlobalView extension of IVS was developed which enables the generation of panoramic images of the environment and a more intuitive control of the camera. The live video frame is superimposed on a 360°static panoramic picture. By interactively moving a rectangular frame in the panoramic picture, the user locally selects the new direction of the camera. Once the view is selected the users prompts the selection and the command is issued over the Internet to the remotely-controlled camera. The static panoramic image is constantly updated in areas where new live video information gets available. Two methods are described for static panoramic image generation: one uses geometric transformation and the other is the brute-force scanning approach. We discuss how visual summaries of activities on an observed location can be generated and custom queries made with a similar intuitive user interface.

Moments of superellipsoids and their application to range image registration

Cartesian moments are frequently used global geometrical features in computer vision for object pose estimation and recognition. We derive a closed form expression for 3-D Cartesian moment of order p+q+r of a superellipsoid in its canonical coordinate system. We also show how 3-D Cartesian moment of a globally deformed superellipsoid in general position and orientation can be computed as a linear combination of 3-D Cartesian moments of the corresponding nondeformed superellipsoid in canonical coordinate system. Additionally, moments of objects that are compositions of superellipsoids can be computed as simple sums of moments of individual parts. To demonstrate practical application of the derived results we register pairs of range images based on moments of recovered compositions of superellipsoids. We use a standard technique to find centers of gravity and principal axes in pairs of range images while third-order moments are used to resolve the four-way ambiguity. Experimental results show expected improvement of recovered rigid transformation based on moments of recovered superellipsoids as compared to the registration based on moments of raw range image data. Besides object pose estimation the presented results can be directly used for object recognition with moments and/or moment invariants as object features.

Panoramic Depth Imaging: Single Standard Camera Approach

In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the cameras optical center from the rotational center of the system we are able to capture the motion parallax effect which enables stereo reconstruction. The camera is rotating on a circular path with a step defined by the angle, equivalent to one pixel column of the captured image. The equation for depth estimation can be easily extracted from the system geometry. To find the corresponding points on a stereo pair of panoramic images the epipolar geometry needs to be determined. It can be shown that the epipolar geometry is very simple if we are doing the reconstruction based on a symmetric pair of stereo panoramic images. We get a symmetric pair of stereo panoramic images when we take symmetric pixel columns on the left and on the right side from the captured image center column. Epipolar lines of the symmetrical pair of panoramic images are image rows. The search space on the epipolar line can be additionaly constrained. The focus of the paper is mainly on the system analysis. Results of the stereo reconstruction procedure and quality evaluation of generated depth images are quite promissing. The system performs well for reconstruction of small indoor spaces. Our finall goal is to develop a system for automatic navigation of a mobile robot in a room.