Geometric and photometric restoration of distorted documents
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: 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: Building large-format displays for digital libraries
abstract: COMMUNICATIONS OF THE ACM May 2001/Vol. 44, No. 5 57 Digital libraries house media of ever-increasing complexity, from models of statues to virtual archeological landscapes. Future digital archives will only increase in resolution and complexity as acquisition hardware improves and data becomes more intricate. Although digital content is constantly improving, the typical display device (the desktop monitor) remains relatively unchanged. The problem is the spatial resolution and color quality of digital media surpasses the display real estate of typical monitors. It is common for objects such as artwork and manuscripts to be digitized at a much higher resolution than can be displayed on even the best monitors. This forces the data to be down-sampled, or restricts viewing to selected regions of interest at a time. Even with improved resolution, small display areas are often less than compelling. For example, the high-resolution facsimile of Michelangelo’s 17-foot statue of David [4] is somewhat less spectacular when displayed on a high-resolution 20-inch monitor. The simple fact is monitors have become under-powered technologies for the visualization capabilities now needed to fully appreciate digital archives. The immediate reaction is to enlist the help of large-format displays for visualization available as video walls, domes, and immersive environments such as the CAVE. These environments provide a compelling sense of presence and help break the “window on worlds” paradigm. Unfortunately, these technologies also present serious challenges that limit their accessibility and usefulness to a small number of institutions. Of primary concern is the cost. Initial costs of projectors, rendering hardware, and subsequent recurring operational expenses are fiscally prohibitive. A second concern is the renovation necessary for installing a large-format display system. Because most systems rely on mechanically aligned projectors and rigidly constructed display surfaces, room modification and projection surface infrastructure are necessary. An additional difficulty is the complexity of continuous operation. These systems are not for novice users and can quickly become unusable without expert maintenance and tuning. Our goal is to bring large-format displays to the digital library community by breaking down the barriers that make them expensive and difficult to set up and run. We are attacking the price/performance barrier by engineering displays built entirely from commodity components and assembled in a scalable configuration. Specifically, commodity light projectors, unlike monitors, can be positioned collectively to form a single logical desktop . Inexpensive video cards can perform at the level required to drive a projector. Groups of PCs, each driving a projector and communicating via a local area network, are inexpensive and powerful [2, 6]. While the physical alignment of projectors creates a very compelling display, it is tedious and requires major effort. Within the digital library community, where libraries must operate and maintain equipment, it is important to enable novice technicians to build up and maintain a display by a more casual placement of projectors. Michael S. Brown, W. Brent Seales, Stephen B. Webb, and Christopher O. Jaynes { {

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: 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: Correcting common distortions in camera-imaged library materials
abstract: We present a technique to correct image distortion that can occur when library materials are imaged by cameras. Our approach provides a general framework to undo a variety of common distortions, including binder curl, fold distortion, and combinations of the two. Our algorithm is described and demonstrated on several examples.

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: 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: Investigating the Relationship between Internet Privacy Concerns and Online Purchase Behavior
abstract: Many organizations now emphasize the use of technology that can help them get closer to consumers and build ongoing relationships with them. The ability to compile consumer data profiles has been made even easier with Internet technology. However, it is often assumed that consumers like to believe they can trust a company with their personal details. Lack of trust may cause consumers to have privacy concerns. Addressing such privacy concerns may therefore be crucial to creating stable and ultimately profitable customer relationships. Three specific privacy concerns that have been frequently identified as being of importance to consumers include unauthorized secondary use of data, invasion of privacy, and errors. Results of a survey study indicate that both errors and invasion of privacy have a significant inverse relationship with online purchase behavior. Unauthorized use of secondary data appears to have little impact. Managerial implications include the careful selection of communication channels for maximum impact, the maintenance of discrete “permission-based” contact with consumers, and accurate recording and handling of data.

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.

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.