Unsupervised 3D object recognition and reconstruction in unordered datasets
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: Recognising panoramas
abstract: The problem considered in this paper is the fully automatic construction of panoramas. Fundamentally, this problem requires recognition, as we need to know which parts of the panorama join up. Previous approaches have used human input or restrictions on the image sequence for the matching step. In this work we use object recognition techniques based on invariant local features to select matching images, and a probabilistic model for verification. Because of this our method is insensitive to the ordering, orientation, scale and illumination of the images. It is also insensitive to 'noise' images which are not part of the panorama at all, that is, it recognises panoramas. This suggests a useful application for photographers: the system takes as input the images on an entire flash card or film, recognises images that form part of a panorama, and stitches them with no user input whatsoever.

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: 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: Visualization in Scientific Computing
abstract: Publisher Summary Computational science and engineering (CSE it enables them to analyze the data to uncover new information. Computational scientists rely upon a host of high-volume data sources in order to conduct their research. However, they are deluged by the flood of data generated. Using an exclusively numerical format, the human brain cannot interpret gigabytes of data each day, so much information now goes to waste. It is impossible for users to ever quantitatively examine more than a tiny fraction of the solution; that is, it is impossible to investigate the qualitative global nature of numeric solutions. Therefore, the ability to visualize complex computations and simulations is absolutely essential to ensure the integrity of analyses, to provoke insights, and to communicate those insights with others. The chapter focuses on visualization. It is a method of computing that gives visual form to complex data. The growing importance of CS&E, especially with supercomputer capabilities, is creating a commensurate need for more sophisticated visual representations of natural phenomena across time. This requires the development of new tool sets for image generation, visual communication, and analysis. The chapter discusses examples of scientific-visualization for facilitating CS&E research specifically in the fields of planetary sciences, molecular modeling, mathematics, and medical Imaging. The chapter also highlights the current limitations and bottlenecks in visualization technology, focusing on software limitations, data management limitation, hardware limitations, educational limitations, and communication and publication limitation.

title: PixelFlex: a reconfigurable multi-projector display system
abstract: This paper presents PixelFlex - a spatially reconfigurable multi-projector display system. The PixelFlex system is composed of ceiling-mounted projectors, each with computer-controlled pan, tilt, zoom and focus; and a camera for closed-loop calibration. Working collectively, these controllable projectors function as a single logical display capable of being easily modified into a variety of spatial formats of differing pixel density, size and shape. New layouts are automatically calibrated within minutes to generate the accurate warping and blending functions needed to produce seamless imagery across planar display surfaces, thus giving the user the flexibility to quickly create, save and restore multiple screen configurations. Overall, PixelFlex provides a new level of automatic reconfigurability and usage, departing from the static, one-size-fits-all design of traditional large-format displays. As a front-projection system, PixelFlex can be installed in most environments with space constraints and requires little or no post-installation mechanical maintenance because of the closed-loop calibration.

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: 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.