RUSHES—an annotation and retrieval engine for multimedia semantic units

Multimedia analysis and reuse of raw un-edited audio visual content known as rushes is gaining acceptance by a large number of research labs and companies. A set of research projects are considering multimedia indexing, annotation, search and retrieval in the context of European funded research, but only the FP6 project RUSHES is focusing on automatic semantic annotation, indexing and retrieval of raw and un-edited audio-visual content. Even professional content creators and providers as well as home-users are dealing with this type of content and therefore novel technologies for semantic search and retrieval are required. In this paper, we present a summary of the most relevant achievements of the RUSHES project, focusing on specific approaches for automatic annotation as well as the main features of the final RUSHES search engine.     

A visual digital library approach for time-oriented scientific primary data

Digital Library support for textual and certain types of non-textual documents has significantly advanced over the last years. While Digital Library support implies many aspects along the whole library workflow model, interactive and visual retrieval allowing effective query formulation and result presentation are important functions. Recently, new kinds of non-textual documents which merit Digital Library support, but yet cannot be fully accommodated by existing Digital Library technology, have come into focus. Scientific data, as produced for example, by scientific experimentation, simulation or observation, is such a document type. In this article we report on a concept and first implementation of Digital Library functionality for supporting visual retrieval and exploration in a specific important class of scientific primary data, namely, time-oriented research data. The approach is developed in an interdisciplinary effort by experts from the library, natural sciences, and visual analytics communities. In addition to presenting the concept and to discussing relevant challenges, we present results from a first implementation of our approach as applied on a real-world scientific primary data set. We also report from initial user feedback obtained during discussions with domain experts from the earth observation sciences, indicating the usefulness of our approach.     

Parallel Iterator for Parallelizing Object-Oriented Applications

With the advent of multi-core processors, desktop application developers must finally face parallel computing and its challenges. A large portion of the computational load in a program rests within iterative computations. In object-oriented languages these are commonly handled using iterators which are inadequate for parallel programming. This paper presents a powerful Parallel Iterator concept to be used in object-oriented programs for the parallel traversal of a collection of elements. The Parallel Iterator may be used with any collection type (even those inherently sequential) and it supports several scheduling schemes which may even be decided dynamically at run-time. Some additional features are provided to allow early termination of parallel loops, exception handling and a solution for performing reductions. With a slight contract modification, the Parallel Iterator interface imitates that of the Java-style sequential iterator. All these features combine together to promote minimal, if any, code restructuring. Along with the ease of use, the results reveal negligible overhead and the expected inherent speedup.     

Tailored least-squares solvers implementation for high-performance gravity field research

Least-squares (LS) problems occur in almost every scientific and engineering discipline. Basically, they are generated by providing more observations than unknown parameters to be resolved. Appropriate LS solvers depend on both quality and computational issues. With regard to the latter, this paper focuses on the tailored parallel implementation of two LS solvers: the iterative LSQR method (substitutional for any Krylov-space method) and the “brute-force” inversion approach. Both implementations demonstrate very good scaling results in a parallel processing environment. Even so, the present investigations show that, from the computational and hardware point of view, iterative solvers outperform the “brute-force” approach. LSQR not only provides superior speed-up values; but, in addition, source code portability and hardware requirements are much more convenient for the iterative solver. These conclusions are drawn in the context of state-of-the-art terrestrial geopotential recovery with regard to the forthcoming Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite mission.     

Adjustable speed surface subdivision

We introduce a non-uniform subdivision algorithm that partitions the neighborhood of an extraordinary point in the ratio σ:1−σ, where σ(0,1). We call σ the speed of the non-uniform subdivision and verify C¹ continuity of the limit surface. For σ=1/2, the Catmull–Clark limit surface is recovered. Other speeds are useful to vary the relative width of the polynomial spline rings generated from extraordinary nodes.     

Considerations about the relationship between animal and machine ethics

Ethics researches morality in respect to humans and animals. Usually, it implies human morality; therefore, the focus is on human–human relationships (generally in ethics) and human–animal relationships (in animal ethics). Ethics can also deal with the morality of machines such as unmanned aerial vehicles, robots and agents or of self-driving cars and computers in automated trading, in other words more or less autonomous systems and programs. Machine ethics almost exclusively concentrates on machine–human relationships rather than on machine–animal relationships. Before this background, this article contributes some basic considerations about the relationship between animal and machine ethics.     

Large area forest stem volume mapping in the boreal zone using synergy of ERS-1/2 tandem coherence and MODIS vegetation continuous fields

ERS-1/2 tandem coherence was reported to have high potential for the mapping of boreal forest stem volume (e.g. Santoro et al., 2002, 2007a; Wagner et al., 2003; Askne & Santoro, 2005). Large-scale application of the data for forest stem volume mapping, however, is hindered by the variability of coherence with meteorological and environmental acquisition conditions. The traditional way of stem volume retrieval is based on the training of models, relating coherence to stem volume, with the aid of forest inventory data which is generally available for a few small test sites but not for large areas. In this paper a new approach is presented that allows model training using the MODIS Vegetation Continuous Fields canopy cover product (Hansen et al., 2003) without further need for ground data. A comparison of the new approach with the traditional regression-based and ground-data dependent model training is presented in this paper for a multi-seasonal ERS-1/2 tandem dataset covering several well known Central Siberian forest sites. As a test scenario for large-area application, the approach was applied to a multi-seasonal ERS-1/2 tandem dataset of 223 ERS-1 and ERS-2 image pairs covering Northeast China (~ 1.5 million km²) to map four stem volume classes (0-20, 20-50, 50-80, and > 80 m³/ha).