Freehand HDR Imaging of Moving Scenes with Simultaneous Resolution Enhancement

Despite their high popularity, common high dynamic range (HDR) methods are still limited in their practical applicability: They assume that the input images are perfectly aligned, which is often violated in practise. Our paper does not only free the user from this unrealistic limitation, but even turns the missing alignment into an advantage: By exploiting the multiple exposures, we can create a super‐resolution image. The alignment step is performed by a modern energy‐based optic flow approach that takes into account the varying exposure conditions. Moreover, it produces dense displacement fields with subpixel precision. As a consequence, our approach can handle arbitrary complex motion patterns, caused by severe camera shake and moving objects. Additionally, it benefits from several advantages over existing strategies: (i) It is robust under outliers (noise, occlusions, saturation problems) and allows for sharp discontinuities in the displacement field. (ii) The alignment step neither requires camera calibration nor knowledge of the exposure times. (iii) It can be efficiently implemented on CPU and GPU architectures. After the alignment is performed, we use the obtained subpixel accurate displacement fields as input for an energy‐based, joint super‐resolution and HDR (SR‐HDR) approach. It introduces robust data terms and anisotropic smoothness terms in the SR‐HDR literature. Our experiments with challenging real world data demonstrate that these novelties are pivotal for the favourable performance of our approach.     

Geometric Spanners for Weighted Point Sets

Let (S,d) be a finite metric space, where each element p∈S has a non-negative weight w (p). We study spanners for the set S with respect to the following weighted distance function:

Efficient Gaussian process classification using random decision forests

Gaussian Processes are powerful tools in machine learning which offer wide applicability in regression and classification problems due to their non-parametric and non-linear behavior. However, one of their main drawbacks is the training time complexity which scales cubically with the number of samples. Our work addresses this issue by combining Gaussian Processes with Randomized Decision Forests to enable fast learning. An important advantage of our method is its simplicity and the ability to directly control the trade-off between classification performance and computation speed. Experiments on an indoor place recognition task show that our method can handle large training sets in reasonable time while retaining a good classification accuracy.     

Queries on Xml streams with bounded delay and concurrency

Query answering algorithms on Xml streams check answer candidates on the fly in order to avoid the unnecessary buffering whenever possible. The delay and concurrency of a query are two measures for the degree of their streamability. They count the maximal number of stream elements during the life time for some query answer, and respectively, the maximal number of simultaneously alive answer candidates of a query. We study queries defined by deterministic nested word automata, which subsume large streamable fragments of XPath subject to schema restrictions by DTDs modulo P-time translations. We show that bounded and k-bounded delay and concurrency of such automata-defined queries are all decidable in polynomial time in the size of the automaton. Our results are obtained by P-time reduction to the bounded valuedness problem for recognizable relations between unranked trees, a problem that we show to be decidable in P-time.     

A new feature extraction method for odour classification

A new method for real time classification of volatile chemical substance traces is presented. The method is based on electrochemical signals of an array of semiconductor gas sensors. In these sensor signals characteristic patterns of different substances are hidden. There are non-linear correlative relationships between the measured sensor signals and the chemical substances which are treated using two methods derived from statistical learning theory (Support Vector Machine - SVM, Maximum Likelihood Estimation - MLE) for the detection of the substance characteristics in the sensor signals. A key criterion for the presented pattern recognition is a newly developed type of features, which is specially adapted to the low frequency signals of semiconductor sensors. The presented features are based on the evaluation of the range of the transient response in the sensor signals in the frequency domain.To derive the new features, both real measurement data and synthetic generated signals were used. In the experiments the focus was set on the creation of reproducible sensor signals to get characteristic signal patterns. Synthetic signals were derived from a Gaussian Plume Model. With the new features, training data sets were calculated using the classification methods SVM and MLE. With these training data sets new sensor measurements may be assigned to the substances which are to be sought. The advantage of the presented method is that no feature reduction is needed and no loss of information occurs in the learning process.The classification results based on the new features have been compared with the classification based on a conventional method for feature extraction. It was proved that the recognition rate of the substances used with the new feature type is higher.The substance classification is primarily limited by the sensitivity of the semiconductor sensors, because sufficiently large sensor signals must have been provided to obtain appropriate substance patterns. At the present stage of development the method presented is suitable for the classification of substance groups, such as nitro aromatics or alcohols, but not for specific substances.     

Benchmarking urban six‐degree‐of‐freedom simultaneous localization and mapping

Quite a number of approaches for solving the simultaneous localization and mapping (SLAM) problem exist by now. Some of them have recently been extended to mapping environments with six‐degree‐of‐freedom poses, yielding 6D SLAM approaches. To demonstrate the capabilities of the respective algorithms, it is common practice to present generated maps and successful loop closings in large outdoor environments. Unfortunately, it is nontrivial to compare different 6D SLAM approaches objectively, because ground truth data about the outdoor environments used for demonstration are typically unavailable. We present a novel benchmarking method for generating the ground truth data based on reference maps. The method is then demonstrated by comparing the absolute performance of some previously existing 6D SLAM algorithms that build a large urban outdoor map. © 2008 Wiley Periodicals, Inc.     

Synthesis and investigation of α,ω-methacryloyl terminated epoxide-amine macromonomers

Summary ,-methacryloyl-poly (epoxide-amine)-macromonomers were synthesized by reaction of bisphenol-A diglycidylether DGEBA and methacrylic acid followed by addition polymerization of unreacted expoxide groups with primary monoamines or disecondary diamines, respectively. The resultant macromonomers having M_n (vpo)-values between 530 and 2000 g/mol were analysed by IR-, ¹H-NMR- and ¹³C-NMR-spectroscopy. HPLC and GPC analysis were used to determine the distribution of oligomers. The macromonomers are glassy or viscous liquids with T_g between 0 and 50 °C depending on the nature of the amine and polymerization degree.     

Wirbelschicht-Technologie: Neuentwicklungen für Kraftwerkstechnik und Umweltschutz

Fluidized bed technology: recent developments for power station engineering and pollution abatement . The principle of fluidization has been successfully applied to numerous areas of chemical engineering. Combustion of coal in a fluidized bed consisting of particles of ash and limestone or dolomite permits low-pollution utilization of coals having lower heating values or high sulphur contents without any need for removing sulphur from the exhaust gases. The present state of the art and world-wide development work on fluidized combustion are considered, as are the future prospects of this new energy technology.