1546062
The digital Michelangelo project: 3D scanning of large statues
We describe a hardware and software system for digitizing the shape and color of large fragile objects under non-laboratory conditions. Our system employs laser triangulation rangefinders, laser time-of-flight rangefinders, digital still cameras, and a suite of software for acquiring, aligning, merging, and viewing scanned data. As a demonstration of this system, we digitized 10 statues by Michelangelo, including the well-known figure of David, two building interiors, and all 1,163 extant fragments of the Forma Urbis Romae, a giant marble map of ancient Rome. Our largest single dataset is of the David - 2 billion polygons and 7,000 color images. In this paper, we discuss the challenges we faced in building this system, the solutions we employed, and the lessons we learned. We focus in particular on the unusual design of our laser triangulation scanner and on the algorithms and software we developed for handling very large scanned models.
8652205
Copy detection mechanisms for digital documents
In a digital library system, documents are available in digital form and therefore are more easily copied and their copyrights are more easily violated. This is a very serious problem, as it discourages owners of valuable information from sharing it with authorized users. There are two main philosophies for addressing this problem: prevention and detection. The former actually makes unauthorized use of documents difficult or impossible while the latter makes it easier to discover such activity.In this paper we propose a system for registering documents and then detecting copies, either complete copies or partial copies. We describe algorithms for such detection, and metrics required for evaluating detection mechanisms (covering accuracy, efficiency, and security). We also describe a working prototype, called COPS, describe implementation issues, and present experimental results that suggest the proper settings for copy detection parameters.
16145112
Mosaics of scenes with moving objects
Image mosaics are useful for a variety of tasks in vision and computer graphics. A particularly convenient way to generate mosaics is by 'stitching' together many ordinary photographs. Existing algorithms focus on capturing static scenes. This paper presents a complete system for creating visually pleasing mosaics in the presence of moving objects. There are three primary contributions. The first component of our system is a registration method that remains unbiased by movement-the Mellin transform is extended to register images related by a projective transform. Second an efficient method for finding a globally consistent registration of all images is developed. By solving a linear system of equations, derived from many pairwise registration matrices, we find an optimal global registration. Lastly, a new method of compositing images is presented. Blurred areas due to moving objects are avoided by segmenting the mosaic into disjoint regions and sampling pixels in each region from a single source image.
1351850
Filling holes in complex surfaces using volumetric diffusion
We address the problem of building watertight 3D models from surfaces that contain holes - for example, sets of range scans that observe most but not all of a surface. We specifically address situations in which the holes are too geometrically and topologically complex to fill using triangulation algorithms. Our solution begins by constructing a signed distance function, the zero set of which defines the surface. Initially, this function is defined only in the vicinity of observed surfaces. We then apply a diffusion process to extend this function through the volume until its zero set bridges whatever holes may be present. If additional information is available, such as known-empty regions of space inferred from the lines of sight to a 3D scanner, it can be incorporated into the diffusion process. Our algorithm is simple to implement, is guaranteed to produce manifold non-interpenetrating surfaces, and is efficient to run on large datasets because computation is limited to areas near holes.
7180811
Calibrating pan-tilt cameras in wide-area surveillance networks
Pan-tilt cameras are often used as components of wide-area surveillance systems. It is necessary to calibrate these cameras in relation to one another in order to obtain a consistent representation of the entire space. Existing methods for calibrating pan-tilt cameras have assumed an idealized model of camera mechanics. In addition, most methods have been calibrated using only a small range of camera motion. We present a method for calibrating pan-tilt cameras that introduces a more complete model of camera motion. Pan and tilt rotations are modeled as occurring around arbitrary axes in space. In addition, the wide area surveillance system itself is used to build a large virtual calibration object, resulting in better calibration than would be possible with a single small calibration target. Finally, the proposed enhancements are validated experimentally, with comparisons showing the improvement provided over more traditional methods.
2294366
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
We present an unsupervised algorithm for registering 3D surface scans of an object undergoing significant deformations. Our algorithm does not need markers, nor does it assume prior knowledge about object shape, the dynamics of its deformation, or scan alignment. The algorithm registers two meshes by optimizing a joint probabilistic model over all point-to-point correspondences between them. This model enforces preservation of local mesh geometry, as well as more global constraints that capture the preservation of geodesic distance between corresponding point pairs. The algorithm applies even when one of the meshes is an incomplete range scan; thus, it can be used to automatically fill in the remaining surfaces for this partial scan, even if those surfaces were previously only seen in a different configuration. We evaluate the algorithm on several real-world datasets, where we demonstrate good results in the presence of significant movement of articulated parts and non-rigid surface deformation. Finally, we show that the output of the algorithm can be used for compelling computer graphics tasks such as interpolation between two scans of a non-rigid object and automatic recovery of articulated object models.
17135898
The Economic Contribution of Software: An Alternative Perspective on the Productivity Paradox
The complex relationships between information technology investments and business value have been the focus of intensive research in recent years. There appears to be a discernible trend toward a more nuanced view in which the differential effects of the various categories of IT capital such as hardware, software, and their interactions with organizational factors are systematically investigated. As well, there is emerging evidence of accelerating investments in software and a greater shift toward “softwarization” (Langdon 2003) in which value addition is linked to combining flexible software with increasingly commoditized hardware. In this paper, we focus on the differential contributions of hardware and software capital and their interactions with labor capital. We use industry-level data to extend previous studies in three ways: (1) by using more recent data (1990 to 2002), (2) by focusing on IT-using industries in the private sector, and (3) by treating IT hardware and IT software as two distinct classes of IT capital. We adopt the commonly used log-linear Cobb Douglas production function approach. Our findings indicate that the impacts of software are significantly different in comparison with hardware and that the productivity benefits attributable to IT are largely due to the interactions between software and labor inputs. We conclude that software is the key to productivity growth in the IT-using world, and show that it can be used as the closest surrogate to represent business complementarities to IT in macro-level studies.
27293359
An Integrated Approach to Learning Bayesian Networks of Rules
Inductive Logic Programming (ILP) is a popular approach for learning rules for classification tasks. An important question is how to combine the individual rules to obtain a useful classifier. In some instances, converting each learned rule into a binary feature for a Bayes net learner improves the accuracy compared to the standard decision list approach [3,4,14]. This results in a two-step process, where rules are generated in the first phase, and the classifier is learned in the second phase. We propose an algorithm that interleaves the two steps, by incrementally building a Bayes net during rule learning. Each candidate rule is introduced into the network, and scored by whether it improves the performance of the classifier. We call the algorithm SAYU for Score As You Use. We evaluate two structure learning algorithms Naive Bayes and Tree Augmented Naive Bayes. We test SAYU on four different datasets and see a significant improvement in two out of the four applications. Furthermore, the theories that SAYU learns tend to consist of far fewer rules than the theories in the two-step approach.
17369120
Informing Public Deliberation: Value Sensitive Design of Indicators for a Large-scale Urban Simulation
We investigate informing public deliberation regarding major land use and transportation decisions with the results from a sophisticated computer simulation of urban development. Our specific focus is on indicators that portray key results from the simulations. Our design addresses a number of challenges, including responding to the values and interests of diverse stakeholders, making documentation ready-to-hand, and balancing the value of fairness with presenting a diverse set of advocacy positions. We use Value Sensitive Design as our theory and design methodology; our theoretical framework also draws on Habermas's theories of legitimation and communicative action. Our work contributes to CSCW as an example of designing a system for effective use in an environment with multiple stakeholders who have fundamental disagreements, and we conclude by drawing lessons for other environments with these characteristics.
17316572
Aligning Ontologies through Formal Concept Analysis
Abstract.Ontologies have been developed for a number of knowledge domains as di-verseasclinicalterminology,photocamerapartsandmicro-arraygeneexpressiondata.However,aninnatecharacteristicofthedevelopmentofontologiesisthattheyareoftencreatedbyindependentgroupsofexpertise,whichgeneratedthenecessityofmergingandaligningontologiescoveringoverlappingdomains.Manyalgorithmsandtoolshavebeenproposedformergingofontologies,butmostofthemdisregardthestructuralpropertiesofthesourceontologies,focusingmostlyonsyntacticanalysis.This article focuses on an alignment method for ontologies based on Formal ConceptAnalysis,adataanalysistechniquefoundedonlatticetheory. 1 Introduction IntheheartofSemanticWebinitiative,proposedbyTimBerners-lee[2,3],liestheideaofmachineprocessableinformation,suchthatautomatedagents,orsoftbots,couldscanthewebspaceforinformationwithaspeciﬂcmeaning.Nevertheless,theunderstandingofmeaninginWebpagesdesignedforhumansisnotaneasytaskforthepresentgenerationofsoftbotsandontologiescangreatlyassistinthisendeavour.Manyinitiativesaroundtheworldhavecreatedontologies.Someoftheseontologieswerecreatedforhighleveldescriptionoftheworld,whereasothersrepresentveryspeciﬂcsub-jects,likebreastcancer,forinstance.Sometimes,ontologiesdevelopedindependentlymayhavesomeoverlaps.TheforementionedBreastCancerOntology,forexample,mayhavecommonconceptsandrelationswithaGeneOntology.Theseoverlapsareveryimpor-tantfromthepointofviewofinformationintegration,becausethecommonontologicalentitieshavetobeidentiﬂedbeforeinformationcanbesuccessfullyintegrated.Forthisreason,mergeandalignmentofontologieshavereceivedsigniﬂcantattentionfromtheresearchcommunityinthelastsixyears.Theﬂrstimportantissueinmerge/alignmentofontologiesistherelationsymbol-meaning.Ontologiesareconstitutedofsymbols(entities)andrelationsbetweensymbols.However,inSemiotics[18]symbolshaveassociatedmeaning,whichlinksthemtotheirreferent
1243996
Real-time closed-world tracking
A real-time tracking algorithm that uses contextual information is described. The method is capable of simultaneously tracking multiple, non-rigid objects when erratic movement and object collisions are common. A closed-world assumption is used to adaptively select and weight image features used for correspondence. Results of algorithm testing and the limitations of the method are discussed. The algorithm has been used to track children in an interactive, narrative playspace.