Language-based multimedia information retrieval

This paper describes various methods and approaches for language-based multimedia information retrieval, which have been developed in the projects POP-EYE and OLIVE and which will be developed further in the MUMIS project. All of these project aim at supporting automated indexing of video material by use of human language technologies. Thus, in contrast to image or sound-based retrieval methods, where both the query language and the indexing methods build on non-linguistic data, these methods attempt to exploit advanced text retrieval technologies for the retrieval of non-textual material. While POP-EYE was building on subtitles or captions as the prime language key for disclosing video fragments, OLIVE is making use of speech recognition to automatically derive transcriptions of the sound tracks, generating time-coded linguistic elements which then serve as the basis for text-based retrieval functionality

On the Use of Historical Bathymetric Data to Determine Changes in Bathymetry: An Analysis of Errors and Application to Great Bay Estuary, NH

The depth measurements that are incorporated into bathymetric charts have associated errors with magnitudes depending on the survey circumstances and applied techniques. For this reason, combining and comparing depth measurements collected over many years with different techniques and standards is a difficult task which must be done with great caution. In this study we have developed an approach for comparing historical bathymetric surveys. Our methodology uses Monte Carlo modelling to account for the random error components inherited in the data due to positioning and depth measurement uncertainties

EChO Payload electronics architecture and SW design

EChO is a three-modules (VNIR, SWIR, MWIR), highly integrated spectrometer, covering the wavelength range from 0.55 $\mu$m, to 11.0 $\mu$m. The baseline design includes the goal wavelength extension to 0.4 $\mu$m while an optional LWIR module extends the range to the goal wavelength of 16.0 $\mu$m. An Instrument Control Unit (ICU) is foreseen as the main electronic subsystem interfacing the spacecraft and collecting data from all the payload spectrometers modules. ICU is in charge of two main tasks: the overall payload control (Instrument Control Function) and the housekeepings and scientific data digital processing (Data Processing Function), including the lossless compression prior to store the science data to the Solid State Mass Memory of the Spacecraft. These two main tasks are accomplished thanks to the Payload On Board Software (P-OBSW) running on the ICU CPUs.Comment: Experimental Astronomy - EChO Special Issue 201

Finding lumbar vertebrae by evidence gathering

Low back pain is a very common problem and lumbar segmental instability is one of the causes. It is essential to investigate lumbar spine movement in order to understand instability better and as an aid to diagnosis. Digital videofluoroscopy (DVF) provides a method of quantifying the motion of individual vertebra. In this paper, we apply a new version of the Hough transform (HT) to locate the lumbar vertebra automatically in DVF image sequences. At present, this algorithm has been applied to a calibration model and to the vertebra L3 in DVF images, and has shown to provide satisfactory results. Further work will concentrate on reducing the computational time for realtime application, on developing a spatiotemporal sequences method and on determining the spinal kinematics based on the extracted parameters

Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

Homologous self-organising scale-invariant properties characterise long range species spread and cancer invasion

The invariance of some system properties over a range of temporal and/or spatial scales is an attribute of many processes in nature1, often characterised by power law functions and fractal geometry2. In particular, there is growing consensus in that fat-tailed functions like the power law adequately describe long-distance dispersal (LDD) spread of organisms 3,4. Here we show that the spatial spread of individuals governed by a power law dispersal function is represented by a clear and unique signature, characterised by two properties: A fractal geometry of the boundaries of patches generated by dispersal with a fractal dimension D displaying universal features, and a disrupted patch size distribution characterised by two different power laws. Analysing patterns obtained by simulations and real patterns from species dispersal and cell spread in cancer invasion we show that both pattern properties are a direct result of LDD and localised dispersal and recruitment, reflecting population self-organisation

Identification of Gastroenteric Viruses by Electron Microscopy Using Higher Order Spectral Features

Background: Many paediatric illnesses are caused by viral agents, for example, acute gastroenteritis. Electron microscopy can provide images of viral particles and can be used to identify the agents. Objectives: The use of electron microscopy as a diagnostic tool is limited by the need for high level of expertise in interpreting these images and the time required. A semi-automated method is proposed in this paper. Study design: The method is based on bispectal features that capture contour and texture information while providing robustness to shift, rotation, changes in size and noise. The magnification or true size of the viral particles need not be known precisely, but if available can be used additionally for improved classification. Viral particles from one or more images are segmented and analyzed to verify whether they belong to a particular class (such as Adenovirus, Rotavirus, etc.) or not. Two experiments were conducted—depending on the populations from which virus particle images were collected for training and testing, respectively. In the first, disjoint subsets from a pooled population of virus particles obtained from several images were used. In the second, separate populations from separate images were used. The performance of the method on viruses of similar size was separately evaluated using Astrovirus, HAV and Poliovirus. A Gaussian Mixture Model was used for the probability density of the features. A threshold on the log-likelihood is varied to study false alarm and false rejection trade-off. Features from many particles and/or likelihoods from independent tests are averaged to yield better performance. Results: An equal error rate (EER) of 2% is obtained for verification of Rotavirus (tested against three other viruses) when features from 15 viral particle images are averaged. It drops further to less than 0.2% when scores from two tests are averaged to make a decision. For verification of Astrovirus (tested against two others of the same size) the EER was less than 2% when 20 particles and two tests were used. Conclusion: Bispectral features and Gaussian mixture modelling of their probability density are shown to be effective in identifying viruses from electron microscope images. With the use of digital imaging in electron microscopes, this method can be fully automated