A practical and flexible tiled display system
Computer graphics and high-resolution digital imagery are becoming increasingly pervasive in communities not traditionally associated with graphics. Commodity graphics cards and digital cameras, along with powerful modeling software, allow organizations such as libraries, museums, and small businesses to produce expressive and realistic computer generated imagery, far surpassing the capabilities of current desktop monitors. What remains elusive to these groups is access to affordable and easy to use large format display technology. We present a practical system for deploying flexible projector based tiled displays. Our framework integrates two key components: (1) self-calibrating display geometry with real-time geometric correction and (2) PC-based distributed rendering that supports an established graphics API. Our system's display geometry is easy to configure and reconfigure, accommodates casually tiled projectors and arbitrary display surfaces, and can be operational in a matter of minutes. In addition, the underlying distributed rendering architecture (WireGL) is transparent to existing OpenGL applications, requiring no custom APIs or re-compilation of existing OpenGL executables. In short, we present a practical and flexible low-cost tiled display system that is simple to deploy and easy to operate.

title: Conformal deskewing of non-planar documents
abstract: This paper presents an approach that uses conformal mapping to parameterize a document's 3D shape to a 2D plane. Using this conformal parametrization, a restorative mapping between an image of the distorted document and a "flattened" representation of the document can be computed and used to deskew the image. Our experiments show that arbitrarily distorted documents can be restored to within a single pixel of their true planar format. In addition, surface points can be constrained to map to specified locations in the restored 2D plane.

title: Geometrically correct imagery for teleconferencing
abstract: Current camera-monitor teleconferencing applications produce unrealistic imagery and break any sense of presence for the participants. Other capture/display technologies can be used to provide more compelling teleconferencing. However, complex geometries in capture/display systems make producing geometrically correct imagery difficult. It is usually impractical to detect, model and compensate for all effects introduced by the capture/display system. Most applications simply ignore these issues and rely on the user acceptance of the camera-monitor paradigm.
This paper presents a new and simple technique for producing geometrically correct imagery for teleconferencing environments. The necessary image transformations are derived by finding a mapping between a capture and display device for a fixed viewer location. The capture/display relationship is computed directly in device coordinates and completely avoids the need for any intermediate, complex representations of screen geometry, capture and display distortions, and viewer location. We describe our approach and demonstrate it via several prototype implementations that operate in real-time and provide a substantially more compelling sense of presence than the standard teleconferencing paradigm.

title: Geometric and photometric restoration of distorted documents
abstract: We present a system to restore the 2D content printed on distorted documents. Our system works by acquiring a 3D scan of the document's surface together with a high-resolution image. Using the 3D surface information and the 2D image, we can ameliorate unwanted surface distortion and effects from non-uniform illumination. Our system can process arbitrary geometric distortions, not requiring any pre-assumed parametric models for the document's geometry. The illumination correction uses the 3D shape to distinguish content edges from illumination edges to recover the 2D content's reflectance image while making no assumptions about light sources and their positions. Results are shown for real objects, demonstrating a complete framework capable of restoring geometric and photometric artifacts on distorted documents

title: Image restoration of arbitrarily warped documents
abstract: We present a framework for acquiring and restoring images of warped documents. The purpose of our restoration is to create a planar representation of a once planar document that has undergone an arbitrary and unknown rigid deformation. To accomplish this restoration, our framework acquires and flattens the 3D shape of a warped document to determine a nonlinear image transform that can correct for image distortion caused by the document's shape. Our framework is designed for use in library and museum digitization efforts where very old and badly damaged manuscripts are imaged.

title: Projected Imagery in Your "Office of the Future"
abstract: Some day, high-resolution projected imagery will surround you in your office. The walls, your desk, and even the floor will serve as your computer desktop.

title: Invariant Features from Interest Point Groups
abstract: This paper approaches the problem of ¯nding correspondences between images in which there are large changes in viewpoint, scale and illumi- nation. Recent work has shown that scale-space `interest points' may be found with good repeatability in spite of such changes. Further- more, the high entropy of the surrounding image regions means that local descriptors are highly discriminative for matching. For descrip- tors at interest points to be robustly matched between images, they must be as far as possible invariant to the imaging process. In this work we introduce a family of features which use groups of interest points to form geometrically invariant descriptors of image regions. Feature descriptors are formed by resampling the image rel- ative to canonical frames de¯ned by the points. In addition to robust matching, a key advantage of this approach is that each match implies a hypothesis of the local 2D (projective) transformation. This allows us to immediately reject most of the false matches using a Hough trans- form. We reject remaining outliers using RANSAC and the epipolar constraint. Results show that dense feature matching can be achieved in a few seconds of computation on 1GHz Pentium III machines.

title: Small Subunit Ribosomal RNA Modeling Using Stochastic Context-Free Grammars
abstract: We introduce a model based on stochastic context-free grammars (SCFGs) that can construct small subunit ribosomal RNA (SSU rRNA) multiple alignments. The method takes into account both primary sequence and secondary structure basepairing interactions. We show that this method produces multiple alignments of quality close to hand edited ones and outperforms several other methods. We also introduce a method of SCFG constraints that dramatically reduces the required computer resources needed to effectively use SCFGs on large problems such as SSU rRNA. Without such constraints, the required computer resources are infeasible for most computers. This work has applications to fields such as phylogenetic tree construction.

title: 3D Model Acquisition by Tracking 2D Wireframes
abstract: This paper presents a semi-automatic wireframe acquisition system. The system uses real-time (25Hz) tracking of a user specified 2D wireframe and intermittent camera pose parameters to accumulate 3D position information. The 2D tracking framework enables the application of model-based constraints in an intuitive way which interacts naturally with the Kalman filter formulation used. In particular, this is used to introduce feedback from the current 3D shape estimate to improve the robustness of the 2D tracking. The scheme allows wireframe models of simple edge based objects to be built in around 5 minutes.

title: User Identification via Keystroke Characteristics of Typed Names using Neural Networks
abstract: A method for identifying computer users by analysing keystroking patterns with neural networks and a simple geometric distance is presented. A model of each user's normal typing style was created and compared with later typing samples. Preliminary results demonstrate complete exclusion of imposters and a reasonably low false alarm rate when the sample text was limited to the user's name.

title: Unsupervised 3D object recognition and reconstruction in unordered datasets
abstract: This paper presents a system for fully automatic recognition and reconstruction of 3D objects in image databases. We pose the object recognition problem as one of finding consistent matches between all images, subject to the constraint that the images were taken from a perspective camera. We assume that the objects or scenes are rigid. For each image, we associate a camera matrix, which is parameterised by rotation, translation and focal length. We use invariant local features to find matches between all images, and the RANSAC algorithm to find those that are consistent with the fundamental matrix. Objects are recognised as subsets of matching images. We then solve for the structure and motion of each object, using a sparse bundle adjustment algorithm. Our results demonstrate that it is possible to recognise and reconstruct 3D objects from an unordered image database with no user input at all.