INLINING 3D RECONSTRUCTION, MULTI-SOURCE TEXTURE MAPPING AND SEMANTIC ANALYSIS USING OBLIQUE AERIAL IMAGERY

This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for fac¸ade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the fac¸ades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained fac¸ade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and conditionally grown, fused and filtered morphologically. The output polygons are vectorized and reintegrated into the previously reconstructed buildings by sparsely ray-tracing their vertices. Finally the enhanced 3D models get stored as textured geometry for visualization and semantically annotated ”LOD-2.5” CityGML objects for GIS applications

In silico Epitope Mapping of Glucose-6-Phosphate Isomerase: A Rheumatoid Arthritis Autoantigen

Rheumatoid arthritis-like symptoms can be initiated experimentally in naive K/BxN mice by simultaneously administering the two monoclonal antibodies 11H3 and 46H9. Both antibodies specifically recognize Glucose-6-Phosphate Isomerase (GPI), a known auto antigen in RA patients. Amino acid sequences of the Fv parts of the antibodies were determined by translating the respective hybridoma DNA sequences and served for threedimensional structure modeling of the paratope regions. In silico docking of both Fv antibody structure models to the X-ray structures of the homodimeric murine GPI as well as to the homodimeric human GPI predicted the murine epitope of the 11H3 antibodies to comprise partial amino acid sequences QRVRSGDWKGYTGKS (aa134-148) and AAKDPSAVAK (aa232-241), generating an assembled (conformational) epitope. The 11H3 epitope on human GPI encompasses the matching partial amino acid sequences QRVRSGDWKGYTGKT (aa134-148) and AAKDPSAVAK (aa232-241). The epitope of the 46H9 antibody was determined to consist of the partial murine GPI amino acid sequence RKELQAAGKSPEDLEK (aa446-461) and the human GPI amino acid sequence RKELQAAGKSPEDLER (aa446-461), respectively, resembling consecutive (linear) epitopes. The predicted epitopes were verified by mass spectrometric epitope mapping using synthetic epitope peptides. Peptide QRVRSGDWKGYTGKS[GSMSGS] AAKDPSAAK included a small spacer sequence in between the epitope sequences, mimicking the assembled epitope for the 11H3 antibody. The peptide RKELQAAGKSPEDLEK represented the consecutive epitope for the 46H9 antibody. The determined B-cell epitopes of GPI and their interactions with the monoclonal antibodies provide a detailed structural understanding of immunological disease onset mechanisms in a mouse model of rheumatoid arthritis

Introduction to the special issue on bibliometric-enhanced information retrieval and natural language processing for digital libraries (BIRNDL)

10.1007/s00799-017-0230-xInternational Journal on Digital Libraries192-Mar107-11

On clustering and polyrepresentation

Polyrepresentation is one of the most prominent principles in a cognitive approach to interactive information seeking and retrieval. When it comes to interactive retrieval, clustering is another method for accessing information. While polyrepresentation has been explored and validated in a scenario where a system returns a ranking of documents, so far there are no insights if and how polyrepresentation and clustering can be combined. In this paper we discuss how both are related and present an approach to integrate polyrepresentation into clustering. We further report some initial evaluation results

Cluster-based polyrepresentation as science modelling approach for information retrieval

The increasing number of publications make searching and accessing the produced literature a challenging task. A recent development in bibliographic databases is to use advanced information retrieval techniques in combination with bibliographic means like citations. In this work we will present an approach that combines a cognitive information retrieval framework based on the principle of polyrepresentation with document clustering to enable the user to explore a collection more interactively than by just examining a ranked result list. Our approach uses information need representations as well as different document representations including citations. To evaluate our ideas we employ a simulated user strategy utilising a cluster ranking approach. We report on the possible effectiveness of our approach and on several strategies how users can achieve a higher search effectiveness through cluster browsing. Our results confirm that our proposed polyrepresentative cluster browsing strategy can in principle significantly improve the search effectiveness. However, further evaluations including a more refined user simulation are needed

How Quantum Theory is Developing the Field of Information Retrieval

This position paper provides an overview of work conducted and an outlook of future directions within the field of In- formation Retrieval (IR) that aims to develop novel models, methods and frameworks inspired by Quantum Theory (QT)

Discovering Novelty Patterns from the Ancient Christian Inscriptions of Rome

Studying Greek and Latin cultural heritage has always been considered essential to the understanding of important aspects of the roots of current European societies. However, only a small fraction of the total production of texts from ancient Greece and Rome has survived up to the present, leaving many gaps in the historiographic records. Epigraphy, which is the study of inscriptions (epigraphs), helps to fill these gaps. In particular, the goal of epigraphy is to clarify the meanings of epigraphs; to classify their uses according to their dating and cultural contexts; and to study aspects of the writing, the writers, and their “consumers.” Although several research projects have recently been promoted for digitally storing and retrieving data and metadata about epigraphs, there has actually been no attempt to apply data mining technologies to discover previously unknown cultural aspects. In this context, we propose to exploit the temporal dimension associated with epigraphs (dating) by applying a data mining method for novelty detection. The main goal is to discover relational novelty patterns—that is, patterns expressed as logical clauses describing significant variations (in frequency) over the different epochs, in terms of relevant features such as language, writing style, and material. As a case study, we considered the set of Inscriptiones Christianae Vrbis Romae stored in Epigraphic Database Bari, an epigraphic repository. Some patterns discovered by the data mining method were easily deciphered by experts since they captured relevant cultural changes, whereas others disclosed unexpected variations, which might be used to formulate new questions, thus expanding the research opportunities in the field of epigraph