Ptolemaic Indexing

This paper discusses a new family of bounds for use in similarity search, related to those used in metric indexing, but based on Ptolemy's inequality, rather than the metric axioms. Ptolemy's inequality holds for the well-known Euclidean distance, but is also shown here to hold for quadratic form metrics in general, with Mahalanobis distance as an important special case. The inequality is examined empirically on both synthetic and real-world data sets and is also found to hold approximately, with a very low degree of error, for important distances such as the angular pseudometric and several Lp norms. Indexing experiments demonstrate a highly increased filtering power compared to existing, triangular methods. It is also shown that combining the Ptolemaic and triangular filtering can lead to better results than using either approach on its own

Visual Image Search: Feature Signatures or/and Global Descriptors

The success of content-based retrieval systems stands or falls with the quality of the utilized similarity model. In the case of having no additional keywords or annotations provided with the multimedia data, the hard task is to guarantee the highest possible retrieval precision using only content-based retrieval techniques. In this paper we push the visual image search a step further by testing effective combination of two orthogonal approaches – the MPEG-7 global visual descriptors and the feature signatures equipped by the Signature Quadratic Form Distance. We investigate various ways of descriptor combinations and evaluate the overall effectiveness of the search on three different image collections. Moreover, we introduce a new image collection, TWIC, designed as a larger realistic image collection providing ground truth. In all the experiments, the combination of descriptors proved its superior performance on all tested collections. Furthermore, we propose a re-ranking variant guaranteeing efficient yet effective image retrieval

Resource Description and Selection for Similarity Search in Metric Spaces: Problems and Problem-Solving Approaches

In times of an ever increasing amount of data and a growing diversity of data types in different application contexts, there is a strong need for large-scale and flexible indexing and search techniques. Metric access methods (MAMs) provide this flexibility, because they only assume that the dissimilarity between two data objects is modeled by a distance metric. Furthermore, scalable solutions can be built with the help of distributed MAMs. Both IF4MI and RS4MI, which are presented in this thesis, represent metric access methods. IF4MI belongs to the group of centralized MAMs. It is based on an inverted file and thus offers a hybrid access method providing text retrieval capabilities in addition to content-based search in arbitrary metric spaces. In opposition to IF4MI, RS4MI is a distributed MAM based on resource description and selection techniques. Here, data objects are physically distributed. However, RS4MI is by no means restricted to a certain type of distributed information retrieval system. Various application fields for the resource description and selection techniques are possible, for example in the context of visual analytics. Due to the metric space assumption, possible application fields go far beyond content-based image retrieval applications which provide the example scenario here.Ständig zunehmende Datenmengen und eine immer größer werdende Vielfalt an Datentypen in verschiedenen Anwendungskontexten erfordern sowohl skalierbare als auch flexible Indexierungs- und Suchtechniken. Metrische Zugriffsstrukturen (MAMs: metric access methods) können diese Flexibilität bieten, weil sie lediglich unterstellen, dass die Distanz zwischen zwei Datenobjekten durch eine Distanzmetrik modelliert wird. Darüber hinaus lassen sich skalierbare Lösungen mit Hilfe verteilter MAMs entwickeln. Sowohl IF4MI als auch RS4MI, die beide in dieser Arbeit vorgestellt werden, stellen metrische Zugriffsstrukturen dar. IF4MI gehört zur Gruppe der zentralisierten MAMs. Diese Zugriffsstruktur basiert auf einer invertierten Liste und repräsentiert daher eine hybride Indexstruktur, die neben einer inhaltsbasierten Ähnlichkeitssuche in beliebigen metrischen Räumen direkt auch Möglichkeiten der Textsuche unterstützt. Im Gegensatz zu IF4MI handelt es sich bei RS4MI um eine verteilte MAM, die auf Techniken der Ressourcenbeschreibung und -auswahl beruht. Dabei sind die Datenobjekte physisch verteilt. RS4MI ist jedoch keineswegs auf die Anwendung in einem bestimmten verteilten Information-Retrieval-System beschränkt. Verschiedene Anwendungsfelder sind für die Techniken zur Ressourcenbeschreibung und -auswahl denkbar, zum Beispiel im Bereich der Visuellen Analyse. Dabei gehen Anwendungsmöglichkeiten weit über den für die Arbeit unterstellten Anwendungskontext der inhaltsbasierten Bildsuche hinaus

A Study of the Structural Similarity Image Quality Measure with Applications to Image Processing

Since its introduction in 2004, the Structural Similarity (SSIM) index has gained widespread popularity as an image quality assessment measure. SSIM is currently recognized to be one of the most powerful methods of assessing the visual closeness of images. That being said, the Mean Squared Error (MSE), which performs very poorly from a perceptual point of view, still remains the most common optimization criterion in image processing applications because of its relative simplicity along with a number of other properties that are deemed important. In this thesis, some necessary tools to assist in the design of SSIM-optimal algorithms are developed. This work combines theoretical developments with experimental research and practical algorithms. The description of the mathematical properties of the SSIM index represents the principal theoretical achievement in this thesis. Indeed, it is demonstrated how the SSIM index can be transformed into a distance metric. Local convexity, quasi-convexity, symmetries and invariance properties are also proved. The study of the SSIM index is also generalized to a family of metrics called normalized (or M-relative) metrics. Various analytical techniques for different kinds of SSIM-based optimization are then devised. For example, the best approximation according to the SSIM is described for orthogonal and redundant basis sets. SSIM-geodesic paths with arclength parameterization are also traced between images. Finally, formulas for SSIM-optimal point estimators are obtained. On the experimental side of the research, the structural self-similarity of images is studied. This leads to the confirmation of the hypothesis that the main source of self-similarity of images lies in their regions of low variance. On the practical side, an implementation of local statistical tests on the image residual is proposed for the assessment of denoised images. Also, heuristic estimations of the SSIM index and the MSE are developed. The research performed in this thesis should lead to the development of state-of-the-art image denoising algorithms. A better comprehension of the mathematical properties of the SSIM index represents another step toward the replacement of the MSE with SSIM in image processing applications

Electronic Imaging & the Visual Arts. EVA 2013 Florence

Important Information Technology topics are presented: multimedia systems, data-bases, protection of data, access to the content. Particular reference is reserved to digital images (2D, 3D) regarding Cultural Institutions (Museums, Libraries, Palace – Monuments, Archaeological Sites). The main parts of the Conference Proceedings regard: Strategic Issues, EC Projects and Related Networks & Initiatives, International Forum on “Culture & Technology”, 2D – 3D Technologies & Applications, Virtual Galleries – Museums and Related Initiatives, Access to the Culture Information. Three Workshops are related to: International Cooperation, Innovation and Enterprise, Creative Industries and Cultural Tourism

Overcoming the Intuition Wall: Measurement and Analysis in Computer Architecture

These are exciting times for computer architecture research. Today there is significant demand to improve the performance and energy-efficiency of emerging, transformative applications which are being hammered out by the hundreds for new computing platforms and usage models. This booming growth of applications and the variety of programming languages used to create them is challenging our ability as architects to rapidly and rigorously characterize these applications. Concurrently, hardware has become more complex with the emergence of accelerators, multicore systems, and heterogeneity caused by further divergence between processor market segments. No one architect can now understand all the complexities of many systems and reason about the full impact of changes or new applications. To that end, this dissertation presents four case studies in quantitative methods. Each case study attacks a different application and proposes a new measurement or analytical technique. In each case study we find at least one surprising or unintuitive result which would likely not have been found without the application of our method

Relativistic Gravitational Experiments in Space

The results are summarized of a workshop on future gravitational physics space missions. The purpose of the workshop was to define generic technological requirements for such missions. NASA will use the results to direct its program of advanced technology development

LIPIcs, Volume 248, ISAAC 2022, Complete Volume

LIPIcs, Volume 248, ISAAC 2022, Complete Volum