Rechenmodelle und Informationssysteme zur Integration großer Windleistungen in die elektrische Energieversorgung

In dieser Arbeit werden verschiedene Computermodelle, Rechenverfahren und Methoden zur Unterstützung bei der Integration großer Windleistungen in die elektrische Energieversorgung entwickelt. Das Rechenmodell zur Simulation der zeitgleich eingespeisten Windenergie erzeugt Summenganglinien von beliebig zusammengestellten Gruppen von Windenergieanlagen, basierend auf gemessenen Wind- und Leistungsdaten der nahen Vergangenheit. Dieses Modell liefert wichtige Basisdaten für die Analyse der Windenergieeinspeisung auch für zukünftige Szenarien. Für die Untersuchung der Auswirkungen von Windenergieeinspeisungen großräumiger Anlagenverbünde im Gigawattbereich werden verschiedene statistische Analysen und anschauliche Darstellungen erarbeitet. Das im Rahmen dieser Arbeit entwickelte Modell zur Berechnung der aktuell eingespeisten Windenergie aus online gemessenen Leistungsdaten repräsentativer Windparks liefert wertvolle Informationen für die Leistungs- und Frequenzregelung der Netzbetreiber. Die zugehörigen Verfahren zur Ermittlung der repräsentativen Standorte und zur Überprüfung der Repräsentativität bilden die Grundlage für eine genaue Abbildung der Windenergieeinspeisung für größere Versorgungsgebiete, basierend auf nur wenigen Leistungsmessungen an Windparks. Ein weiteres wertvolles Werkzeug für die optimale Einbindung der Windenergie in die elektrische Energieversorgung bilden die Prognosemodelle, die die kurz- bis mittelfristig zu erwartende Windenergieeinspeisung ermitteln. In dieser Arbeit werden, aufbauend auf vorangegangenen Forschungsarbeiten, zwei, auf Künstlich Neuronalen Netzen basierende Modelle vorgestellt, die den zeitlichen Verlauf der zu erwarten Windenergie für Netzregionen und Regelzonen mit Hilfe von gemessenen Leistungsdaten oder prognostizierten meteorologischen Parametern zur Verfügung stellen. Die softwaretechnische Zusammenfassung des Modells zur Berechnung der aktuell eingespeisten Windenergie und der Modelle für die Kurzzeit- und Folgetagsprognose bietet eine attraktive Komplettlösung für die Einbindung der Windenergie in die Leitwarten der Netzbetreiber. Die dabei entwickelten Schnittstellen und die modulare Struktur des Programms ermöglichen eine einfache und schnelle Implementierung in beliebige Systemumgebungen. Basierend auf der Leistungsfähigkeit der Online- und Prognosemodelle werden Betriebsführungsstrategien für zu Clustern im Gigawattbereich zusammengefasste Windparks behandelt, die eine nach ökologischen und betriebswirtschaftlichen Gesichtspunkten sowie nach Aspekten der Versorgungssicherheit optimale Einbindung der geplanten Offshore-Windparks ermöglichen sollen.

Design, implementation and application of a generic framework for integrated regional land-use modeling

Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

{2p_\pi}-{2p_\sigma} crossing in heavy symmetric ion-atom collisions: I. Level structure

Ab initio self-consistent DFS calculations are performed for five different symmetric atomic systems from Ar-Ar to Pb-Pb. The level structure for the {2p_\pi}-{2p_\sigma} crossing as function of the united atomic charge Z_u is studied and interpreted. Manybody effects, spin-orbit splitting, direct relativistic effects as well as indirect relativistic effects are differently important for different Z_u. For the I-I system a comparison with other calculations is given.

Non-relativistic and relativistic molecular calculations for the chalcogen hexafluorides: SF_6, SeF_6, TeF_6, PoF_6

Non-relativistic Hartree-Fock-Slater and relativistic Dirac-Slater self-consistent orbital models are applied for the analysis of the electronic structure of the chalcogen hexafluorides: SF_6, SeF_6, TeF_6 and PoF_6. The molecular eigenfunctions and eigenvalues are generated using the discrete variational method (DVM) with numerical basis functions. The results obtained for SF_6 are compared with other ab initio calculations. Information about relativistic level shifts and spin-orbit splitting has been obtained by comparison between the non-relativistic and relativistic results.

Verfahren zur echtzeitfähigen Simulation dynamischer Emissionsverläufe ausgewählter Schadstoffe von Ottomotoren

Im Rahmen dieser Arbeit werden Modellbildungsverfahren zur echtzeitfähigen Simulation wichtiger Schadstoffkomponenten im Abgasstrom von Verbrennungsmotoren vorgestellt. Es wird ein ganzheitlicher Entwicklungsablauf dargestellt, dessen einzelne Schritte, beginnend bei der Ver-suchsplanung über die Erstellung einer geeigneten Modellstruktur bis hin zur Modellvalidierung, detailliert beschrieben werden. Diese Methoden werden zur Nachbildung der dynamischen Emissi-onsverläufe relevanter Schadstoffe des Ottomotors angewendet. Die abgeleiteten Emissionsmodelle dienen zusammen mit einer Gesamtmotorsimulation zur Optimierung von Betriebstrategien in Hybridfahrzeugen. Im ersten Abschnitt der Arbeit wird eine systematische Vorgehensweise zur Planung und Erstellung von komplexen, dynamischen und echtzeitfähigen Modellstrukturen aufgezeigt. Es beginnt mit einer physikalisch motivierten Strukturierung, die eine geeignete Unterteilung eines Prozessmodells in einzelne überschaubare Elemente vorsieht. Diese Teilmodelle werden dann, jeweils ausgehend von einem möglichst einfachen nominalen Modellkern, schrittweise erweitert und ermöglichen zum Abschluss eine robuste Nachbildung auch komplexen, dynamischen Verhaltens bei hinreichender Genauigkeit. Da einige Teilmodelle als neuronale Netze realisiert werden, wurde eigens ein Verfah-ren zur sogenannten diskreten evidenten Interpolation (DEI) entwickelt, das beim Training einge-setzt, und bei minimaler Messdatenanzahl ein plausibles, also evidentes Verhalten experimenteller Modelle sicherstellen kann. Zum Abgleich der einzelnen Teilmodelle wurden statistische Versuchs-pläne erstellt, die sowohl mit klassischen DoE-Methoden als auch mittels einer iterativen Versuchs-planung (iDoE ) generiert wurden. Im zweiten Teil der Arbeit werden, nach Ermittlung der wichtigsten Einflussparameter, die Model-strukturen zur Nachbildung dynamischer Emissionsverläufe ausgewählter Abgaskomponenten vor-gestellt, wie unverbrannte Kohlenwasserstoffe (HC), Stickstoffmonoxid (NO) sowie Kohlenmono-xid (CO). Die vorgestellten Simulationsmodelle bilden die Schadstoffkonzentrationen eines Ver-brennungsmotors im Kaltstart sowie in der anschließenden Warmlaufphase in Echtzeit nach. Im Vergleich zur obligatorischen Nachbildung des stationären Verhaltens wird hier auch das dynami-sche Verhalten des Verbrennungsmotors in transienten Betriebsphasen ausreichend korrekt darge-stellt. Eine konsequente Anwendung der im ersten Teil der Arbeit vorgestellten Methodik erlaubt, trotz einer Vielzahl von Prozesseinflussgrößen, auch hier eine hohe Simulationsqualität und Ro-bustheit. Die Modelle der Schadstoffemissionen, eingebettet in das dynamische Gesamtmodell eines Ver-brennungsmotors, werden zur Ableitung einer optimalen Betriebsstrategie im Hybridfahrzeug ein-gesetzt. Zur Lösung solcher Optimierungsaufgaben bieten sich modellbasierte Verfahren in beson-derer Weise an, wobei insbesondere unter Verwendung dynamischer als auch kaltstartfähiger Mo-delle und der damit verbundenen Realitätsnähe eine hohe Ausgabequalität erreicht werden kann.

Large-Size AlGaN/GaN HEMT Large-Signal Electrothermal Characterization and Modeling for Wireless Digital Communications

The rapid growth in high data rate communication systems has introduced new high spectral efficient modulation techniques and standards such as LTE-A (long term evolution-advanced) for 4G (4th generation) systems. These techniques have provided a broader bandwidth but introduced high peak-to-average power ratio (PAR) problem at the high power amplifier (HPA) level of the communication system base transceiver station (BTS). To avoid spectral spreading due to high PAR, stringent requirement on linearity is needed which brings the HPA to operate at large back-off power at the expense of power efficiency. Consequently, high power devices are fundamental in HPAs for high linearity and efficiency. Recent development in wide bandgap power devices, in particular AlGaN/GaN HEMT, has offered higher power level with superior linearity-efficiency trade-off in microwaves communication. For cost-effective HPA design to production cycle, rigorous computer aided design (CAD) AlGaN/GaN HEMT models are essential to reflect real response with increasing power level and channel temperature. Therefore, large-size AlGaN/GaN HEMT large-signal electrothermal modeling procedure is proposed. The HEMT structure analysis, characterization, data processing, model extraction and model implementation phases have been covered in this thesis including trapping and self-heating dispersion accounting for nonlinear drain current collapse. The small-signal model is extracted using the 22-element modeling procedure developed in our department. The intrinsic large-signal model is deeply investigated in conjunction with linearity prediction. The accuracy of the nonlinear drain current has been enhanced through several issues such as trapping and self-heating characterization. Also, the HEMT structure thermal profile has been investigated and corresponding thermal resistance has been extracted through thermal simulation and chuck-controlled temperature pulsed I(V) and static DC measurements. Higher-order equivalent thermal model is extracted and implemented in the HEMT large-signal model to accurately estimate instantaneous channel temperature. Moreover, trapping and self-heating transients has been characterized through transient measurements. The obtained time constants are represented by equivalent sub-circuits and integrated in the nonlinear drain current implementation to account for complex communication signals dynamic prediction. The obtained verification of this table-based large-size large-signal electrothermal model implementation has illustrated high accuracy in terms of output power, gain, efficiency and nonlinearity prediction with respect to standard large-signal test signals.

Parameter identification of structural dynamic models by inverse statistical analysis

Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.

Effects of different tillage treatments on labile soil organic matter pools and stabilization processes

An improved understanding of soil organic carbon (Corg) dynamics in interaction with the mechanisms of soil structure formation is important in terms of sustainable agriculture and reduction of environmental costs of agricultural ecosystems. However, information on physical and chemical processes influencing formation and stabilization of water stable aggregates in association with Corg sequestration is scarce. Long term soil experiments are important in evaluating open questions about management induced effects on soil Corg dynamics in interaction with soil structure formation. The objectives of the present thesis were: (i) to determine the long term impacts of different tillage treatments on the interaction between macro aggregation (>250 µm) and light fraction (LF) distribution and on C sequestration in plots differing in soil texture and climatic conditions. (ii) to determine the impact of different tillage treatments on temporal changes in the size distribution of water stable aggregates and on macro aggregate turnover. (iii) to evaluate the macro aggregate rebuilding in soils with varying initial Corg contents, organic matter (OM) amendments and clay contents in a short term incubation experiment. Soil samples were taken in 0-5 cm, 5-25 cm and 25-40 cm depth from up to four commercially used fields located in arable loess regions of eastern and southern Germany after 18-25 years of different tillage treatments with almost identical experimental setups per site. At each site, one large field with spatially homogenous soil properties was divided into three plots. One of the following three tillage treatments was carried in each plot: (i) Conventional tillage (CT) with annual mouldboard ploughing to 25-30 cm (ii) mulch tillage (MT) with a cultivator or disc harrow 10-15 cm deep, and (iii) no tillage (NT) with direct drilling. The crop rotation at each site consisted of sugar beet (Beta vulgaris L.) - winter wheat (Triticum aestivum L.) - winter wheat. Crop residues were left on the field and crop management was carried out following the regional standards of agricultural practice. To investigate the above mentioned research objectives, three experiments were conducted: Experiment (i) was performed with soils sampled from four sites in April 2010 (wheat stand). Experiment (ii) was conducted with soils sampled from three sites in April 2010, September 2011 (after harvest or sugar beet stand), November 2011 (after tillage) and April 2012 (bare soil or wheat stand). An incubation study (experiment (iii)) was performed with soil sampled from one site in April 2010. Based on the aforementioned research objectives and experiments the main findings were: (i) Consistent results were found between the four long term tillage fields, varying in texture and climatic conditions. Correlation analysis of the yields of macro aggregate against the yields of free LF ( ≤1.8 g cm-3) and occluded LF, respectively, suggested that the effective litter translocation in higher soil depths and higher litter input under CT and MT compensated in the long term the higher physical impact by tillage equipment than under NT. The Corg stocks (kg Corg m−2) in 522 kg soil, based on the equivalent soil mass approach (CT: 0–40 cm, MT: 0–38 cm, NT: 0–36 cm) increased in the order CT (5.2) = NT (5.2) < MT (5.7). Significantly (p ≤ 0.05) highest Corg stocks under MT were probably a result of high crop yields in combination with reduced physical tillage impact and effective litter incorporation, resulting in a Corg sequestration rate of 31 g C-2 m-2 yr-1. (ii) Significantly higher yields of macro aggregates (g kg-2 soil) under NT (732-777) and MT (680-726) than under CT (542-631) were generally restricted to the 0-5 cm sampling depth for all sampling dates. Temporal changes on aggregate size distribution were only small and no tillage induced net effect was detectable. Thus, we assume that the physical impact by tillage equipment was only small or the impact was compensated by a higher soil mixing and effective litter translocation into higher soil depths under CT, which probably resulted in a high re aggregation. (iii) The short term incubation study showed that macro aggregate yields (g kg-2 soil) were higher after 28 days in soils receiving OM (121.4-363.0) than in the control soils (22.0-52.0), accompanied by higher contents of microbial biomass carbon and ergosterol. Highest soil respiration rates after OM amendments within the first three days of incubation indicated that macro aggregate formation is a fast process. Most of the rebuilt macro aggregates were formed within the first seven days of incubation (42-75%). Nevertheless, it was ongoing throughout the entire 28 days of incubation, which was indicated by higher soil respiration rates at the end of the incubation period in OM amended soils than in the control soils. At the same time, decreasing carbon contents within macro aggregates over time indicated that newly occluded OM within the rebuilt macro aggregates served as Corg source for microbial biomass. The different clay contents played only minor role in macro aggregate formation under the particular conditions of the incubation study. Overall, no net changes on macro aggregation were identified in the short term. Furthermore, no indications for an effective Corg sequestration on the long term under NT in comparison to CT were found. The interaction of soil disturbance, litter distribution and the fast re aggregation suggested that a distinct steady state per tillage treatment in terms of soil aggregation was established. However, continuous application of MT with a combination of reduced physical tillage impact and effective litter incorporation may offer some potential in improving the soil structure and may therefore prevent incorporated LF from rapid decomposition and result in a higher C sequestration on the long term.

Generic Finite Element Model for Mechanically Consistent Scaling of Composite Beam-to-column Joint with Welded Connection

To study the behaviour of beam-to-column composite connection more sophisticated finite element models is required, since component model has some severe limitations. In this research a generic finite element model for composite beam-to-column joint with welded connections is developed using current state of the art local modelling. Applying mechanically consistent scaling method, it can provide the constitutive relationship for a plane rectangular macro element with beam-type boundaries. Then, this defined macro element, which preserves local behaviour and allows for the transfer of five independent states between local and global models, can be implemented in high-accuracy frame analysis with the possibility of limit state checks. In order that macro element for scaling method can be used in practical manner, a generic geometry program as a new idea proposed in this study is also developed for this finite element model. With generic programming a set of global geometric variables can be input to generate a specific instance of the connection without much effort. The proposed finite element model generated by this generic programming is validated against testing results from University of Kaiserslautern. Finally, two illustrative examples for applying this macro element approach are presented. In the first example how to obtain the constitutive relationships of macro element is demonstrated. With certain assumptions for typical composite frame the constitutive relationships can be represented by bilinear laws for the macro bending and shear states that are then coupled by a two-dimensional surface law with yield and failure surfaces. In second example a scaling concept that combines sophisticated local models with a frame analysis using a macro element approach is presented as a practical application of this numerical model.

Effects of grassland conversion and tillage intensities on soil microbial biomass, residues and community structure

Agricultural intensification has a strong impact on level of soil organic matter (SOM), microbial biomass stocks and microbial community structure in agro-ecosystems. The size of the microbial necromass C pool could be about 40 times that of the living microbial biomass C pool in soils. Due to the specificity, amino sugar analysis gives more important information on the relative contribution of fungal and bacterial residues to C sequestration potential of soils. Meanwhile, the relationship between microbial biomass and microbial necromass in soil and its ecological significance on SOM are not fully understood and likely to be very complex in grassland soils. This thesis focuses on the effects of tillage, grassland conversion intensities and fertilisation on microbial biomass, residues and community structure. The combined analyses of microbial biomass and residue formation of both fungi and bacteria provided a unique opportunity to study the effect of tillage, grassland conversion and fertilisation on soil microbial dynamics. In top soil at 0-30 cm layer, a reduction in tillage intensity by the GRT and NT treatments increased the accumulation of saprotrophic fungi in comparison with the MBT treatment. In contrast, the GRT and NT treatments promoted AMF at the expense of saprotrophic fungi in the bottom soil layer at 30-40 cm depth. The negative relationship between the ergosterol to microbial biomass C ratio and the fungal C to bacterial C ratio points to the importance of the relationship between saprotrophic fungi and biotrophic AMF for tillage-induced changes in microbial turnover of SOC. One-season cultivation of winter wheat with two tillage events led to a significant loss in SOC and microbial biomass C stocks at 0-40 cm depth in comparison with the permanent grassland, even 5 years after the tillage event. However, the tillage induced loss in microbial biomass C was roughly 40% less in the long-term than in the short-term of the current experiment, indicating a recovery process during grassland restoration. In general, mould board tillage and grassland conversion to maize monoculture promoted saprotrophic fungi at the expense of biotrophic AMF and bacteria compared to undisturbed grassland soils. Slurry application promoted bacterial residues as indicated by the decreases in both, the ergosterol to microbial biomass C ratio and the fungal C to bacterial C ratio. In addition, the lost microbial functional diversity due to tillage and maize monoculture was restored by slurry application both in arable and grassland soils. I conclude that the microbial biomass C/S ratio can be used as an additional indicator for a shift in microbial community. The strong relationships between microbial biomass and necromass indices points to the importance of saprotrophic fungi and biotrophic AMF for agricultural management induced effects on microbial turnover and ecosystem C storage. Quantitative information on exact biomass estimates of these two important fungal groups in soil is inevitably necessary to understand their different roles in SOM dynamics.

Reforming Cooperative Credit Structure in India for Financial Inclusion

In the drive for financial inclusion in India, cooperative banks assume prime importance as they are much more accessible to the rural poor than commercial banks. While more accessible, cooperative banks' financial health is rather poor and, therefore, might not be able to serve the needy in a sustained manner. A committee led by Prof. Vaidyanathan has outlined a revival package for cooperatives. Besides suggesting an infusion of funds, it called for the adherence to certain stringent norms to ensure the financial viability. The recommendations provided in the committee’s report are under various stages of implementation in India. The book examines the progress of this reform drive in Bihar, a state in Eastern India. It discusses the background for appointing the committee and its recommendations and also presents the findings of a field study conducted in this regard. The findings inform further policy suggestions which are of general interest to the drive for financial inclusion also in other countries.

A Statistical Image-Based Shape Model for Visual Hull Reconstruction and 3D Structure Inference

We present a statistical image-based shape + structure model for Bayesian visual hull reconstruction and 3D structure inference. The 3D shape of a class of objects is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes are then estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We show how the use of a class-specific prior in a visual hull reconstruction can reduce the effect of segmentation errors from the silhouette extraction process. The proposed method is applied to a data set of pedestrian images, and improvements in the approximate 3D models under various noise conditions are shown. We further augment the shape model to incorporate structural features of interest; unknown structural parameters for a novel set of contours are then inferred via the Bayesian reconstruction process. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a data set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

Geometric Structure of the Adaptive Controller of the Human Arm

The objects with which the hand interacts with may significantly change the dynamics of the arm. How does the brain adapt control of arm movements to this new dynamic? We show that adaptation is via composition of a model of the task's dynamics. By exploring generalization capabilities of this adaptation we infer some of the properties of the computational elements with which the brain formed this model: the elements have broad receptive fields and encode the learned dynamics as a map structured in an intrinsic coordinate system closely related to the geometry of the skeletomusculature. The low--level nature of these elements suggests that they may represent asset of primitives with which a movement is represented in the CNS.

Statistical Models for Co-occurrence Data

Modeling and predicting co-occurrences of events is a fundamental problem of unsupervised learning. In this contribution we develop a statistical framework for analyzing co-occurrence data in a general setting where elementary observations are joint occurrences of pairs of abstract objects from two finite sets. The main challenge for statistical models in this context is to overcome the inherent data sparseness and to estimate the probabilities for pairs which were rarely observed or even unobserved in a given sample set. Moreover, it is often of considerable interest to extract grouping structure or to find a hierarchical data organization. A novel family of mixture models is proposed which explain the observed data by a finite number of shared aspects or clusters. This provides a common framework for statistical inference and structure discovery and also includes several recently proposed models as special cases. Adopting the maximum likelihood principle, EM algorithms are derived to fit the model parameters. We develop improved versions of EM which largely avoid overfitting problems and overcome the inherent locality of EM--based optimization. Among the broad variety of possible applications, e.g., in information retrieval, natural language processing, data mining, and computer vision, we have chosen document retrieval, the statistical analysis of noun/adjective co-occurrence and the unsupervised segmentation of textured images to test and evaluate the proposed algorithms.

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence