Fluorescence studies on the 3d-ionization threshold range in krypton

Krypton atoms were excited by photons in the energy range from the threshold for photoionization of the 3d-electrons up to 120 eV. and the fluorescence radiation in the spectral range from 780 to 965 A was observed and analyzed. Cross sections for the population of excited states in KrIII with at least one 4s-hole resulting from an Auger transition as the first decay step and for KrII satellites were determined. The energy dependence of the 3d-ionization cross section in the 3d{_5/2}- and the 3d{_3/2}-threshold range was derived from the experimental data. The cross sections for production of KrII states were found to follow the energy dependence of the 3d-cross sections.

Study of 3d - 4f and 3d - 5f quartet and doublet transitions of doubly excited three-electron ions

We present the first observation of optical transitions between doubly excited doublet states in the term systems N V, 0 VI and F VII. The spectra were produced by foil excitation of fast ion beams. The assignment of the spectral lines was made by comparison with the results of MCDP calculations along the isoelectronic sequence. The same method also led to the identification of two 3d - 4f quartet transitions in Mg X.

3D Simultaneous Inversion for Seismic Structure and Local Hypocenters in Germany under Consideration of Seismic Anisotropy in the Upper Mantel

The main task of this work has been to investigate the effects of anisotropy onto the propagation of seismic waves along the Upper Mantle below Germany and adjacent areas. Refraction- and reflexion seismic experiments proved the existence of Upper Mantle anisotropy and its influence onto the propagation of Pn-waves. By the 3D tomographic investigations that have been done here for the crust and the upper mantle, considering the influence of anisotropy, a gap for the investigations in Europe has been closed. These investigations have been done with the SSH-Inversionprogram of Prof. Dr. M. Koch, which is able to compute simultaneously the seismic structure and hypocenters. For the investigation, a dataset has been available with recordings between the years 1975 to 2003 with a total of 60249 P- and 54212 S-phase records of 10028 seismic events. At the beginning, a precise analysis of the residuals (RES, the difference between calculated and observed arrivaltime) has been done which confirmed the existence of anisotropy for Pn-phases. The recognized sinusoidal distribution has been compensated by an extension of the SSH-program by an ellipse with a slow and rectangular fast axis with azimuth to correct the Pn-velocities. The azimuth of the fast axis has been fixed by the application of the simultaneous inversion at 25° - 27° with a variation of the velocities at +- 2.5 about an average value at 8 km/s. This new value differs from the old one at 35°, recognized in the initial residual analysis. This depends on the new computed hypocenters together with the structure. The application of the elliptical correction has resulted in a better fit of the vertical layered 1D-Model, compared to the results of preceding seismological experiments and 1D and 2D investigations. The optimal result of the 1D-inversion has been used as initial starting model for the 3D-inversions to compute the three dimensional picture of the seismic structure of the Crust and Upper Mantle. The simultaneous inversion has showed an optimization of the relocalization of the hypocenters and the reconstruction of the seismic structure in comparison to the geology and tectonic, as described by other investigations. The investigations for the seismic structure and the relocalization have been confirmed by several different tests. First, synthetic traveltime data are computed with an anisotropic variation and inverted with and without anisotropic correction. Further, tests with randomly disturbed hypocenters and traveltime data have been proceeded to verify the influence of the initial values onto the relocalization accuracy and onto the seismic structure and to test for a further improvement by the application of the anisotropic correction. Finally, the results of the work have been applied onto the Waldkirch earthquake in 2004 to compare the isotropic and the anisotropic relocalization with the initial optimal one to verify whether there is some improvement.

Optimierung der laserinduzierten Plasmaspektroskopie an Metallen durch Femtosekunden-Doppelpulse für die Entwicklung eines hochauflösenden 3D-Rasterabbildungsverfahrens

Die laserinduzierte Plasmaspektroskopie (LIPS) ist eine spektrochemische Elementanalyse zur Bestimmung der atomaren Zusammensetzung einer beliebigen Probe. Für die Analyse ist keine spezielle Probenpräparation nötig und kann unter atmosphärischen Bedingungen an Proben in jedem Aggregatzustand durchgeführt werden. Femtosekunden Laserpulse bieten die Vorteile einer präzisen Ablation mit geringem thermischen Schaden sowie einer hohen Reproduzierbarkeit. Damit ist fs-LIPS ein vielversprechendes Werkzeug für die Mikroanalyse technischer Proben, insbesondere zur Untersuchung ihres Ermüdungsverhaltens. Dabei ist interessant, wie sich die initiierten Mikrorisse innerhalb der materialspezifschen Struktur ausbreiten. In der vorliegenden Arbeit sollte daher ein schnelles und einfach zu handhabendes 3D-Rasterabbildungsverfahren zur Untersuchung der Rissausbreitung in TiAl, einer neuen Legierungsklasse, entwickelt werden. Dazu wurde fs-LIPS (30 fs, 785 nm) mit einem modifizierten Mikroskopaufbau (Objektiv: 50x/NA 0.5) kombiniert, welcher eine präzise, automatisierte Probenpositionierung ermöglicht. Spektrochemische Sensitivität und räumliches Auflösungsvermögen wurden in energieabhängigen Einzel- und Multipulsexperimenten untersucht. 10 Laserpulse pro Position mit einer Pulsenergie von je 100 nJ führten in TiAl zum bestmöglichen Kompromiss aus hohem S/N-Verhältnis von 10:1 und kleinen Lochstrukturen mit inneren Durchmessern von 1.4 µm. Die für das Verfahren entscheidende laterale Auflösung, dem minimalen Lochabstand bei konstantem LIPS-Signal, beträgt mit den obigen Parametern 2 µm und ist die bislang höchste bekannte Auflösung einer auf fs-LIPS basierenden Mikro-/Mapping-Analyse im Fernfeld. Fs-LIPS Scans von Teststrukturen sowie Mikrorissen in TiAl demonstrieren eine spektrochemische Sensitivität von 3 %. Scans in Tiefenrichtung erzielen mit denselben Parametern eine axiale Auflösung von 1 µm. Um die spektrochemische Sensitivität von fs-LIPS zu erhöhen und ein besseres Verständnis für die physikalischen Prozesse während der Laserablation zu erhalten, wurde in Pump-Probe-Experimenten untersucht, in wieweit fs-Doppelpulse den laserinduzierten Abtrag sowie die Plasmaemission beeinflussen. Dazu wurden in einem Mach-Zehnder-Interferometer Pulsabstände von 100 fs bis 2 ns realisiert, Gesamtenergie und Intensitätsverhältnis beider Pulse variiert sowie der Einfluss der Materialparameter untersucht. Sowohl das LIPS-Signal als auch die Lochstrukturen zeigen eine Abhängigkeit von der Verzögerungszeit. Diese wurden in vier verschiedene Regimes eingeteilt und den physikalischen Prozessen während der Laserablation zugeordnet: Die Thermalisierung des Elektronensystems für Pulsabstände unter 1 ps, Schmelzprozesse zwischen 1 und 10 ps, der Beginn des Abtrags nach mehreren 10 ps und die Expansion der Plasmawolke nach über 100 ps. Dabei wird das LIPS-Signal effizient verstärkt und bei 800 ps maximal. Die Lochdurchmesser ändern sich als Funktion des Pulsabstands wenig im Vergleich zur Tiefe. Die gesamte Abtragsrate variiert um maximal 50 %, während sich das LIPS-Signal vervielfacht: Für Ti und TiAl typischerweise um das Dreifache, für Al um das 10-fache. Die gemessenen Transienten zeigen eine hohe Reproduzierbarkeit, jedoch kaum eine Energie- bzw. materialspezifische Abhängigkeit. Mit diesen Ergebnissen wurde eine gezielte Optimierung der DP-LIPS-Parameter an Al durchgeführt: Bei einem Pulsabstand von 800 ps und einer Gesamtenergie von 65 nJ (vierfach über der Ablationsschwelle) wurde eine 40-fache Signalerhöhung bei geringerem Rauschen erzielt. Die Lochdurchmesser vergrößerten sich dabei um 44 % auf (650±150) nm, die Lochtiefe um das Doppelte auf (100±15) nm. Damit war es möglich, die spektrochemische Sensitivität von fs-LIPS zu erhöhen und gleichzeitig die hohe räumliche Auflösung aufrecht zu erhalten.

Region-Based Feature Interpretation for Recognizing 3D Models in 2D Images

In model-based vision, there are a huge number of possible ways to match model features to image features. In addition to model shape constraints, there are important match-independent constraints that can efficiently reduce the search without the combinatorics of matching. I demonstrate two specific modules in the context of a complete recognition system, Reggie. The first is a region-based grouping mechanism to find groups of image features that are likely to come from a single object. The second is an interpretive matching scheme to make explicit hypotheses about occlusion and instabilities in the image features.

Geometry and Photometry in 3D Visual Recognition

The report addresses the problem of visual recognition under two sources of variability: geometric and photometric. The geometric deals with the relation between 3D objects and their views under orthographic and perspective projection. The photometric deals with the relation between 3D matte objects and their images under changing illumination conditions. Taken together, an alignment-based method is presented for recognizing objects viewed from arbitrary viewing positions and illuminated by arbitrary settings of light sources.

Attentional Selection in Object Recognition

A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.

2D-3D Rigid-Body Registration of X-Ray Fluoroscopy and CT Images

The registration of pre-operative volumetric datasets to intra- operative two-dimensional images provides an improved way of verifying patient position and medical instrument loca- tion. In applications from orthopedics to neurosurgery, it has a great value in maintaining up-to-date information about changes due to intervention. We propose a mutual information- based registration algorithm to establish the proper align- ment. For optimization purposes, we compare the perfor- mance of the non-gradient Powell method and two slightly di erent versions of a stochastic gradient ascent strategy: one using a sparsely sampled histogramming approach and the other Parzen windowing to carry out probability density approximation. Our main contribution lies in adopting the stochastic ap- proximation scheme successfully applied in 3D-3D registra- tion problems to the 2D-3D scenario, which obviates the need for the generation of full DRRs at each iteration of pose op- timization. This facilitates a considerable savings in compu- tation expense. We also introduce a new probability density estimator for image intensities via sparse histogramming, de- rive gradient estimates for the density measures required by the maximization procedure and introduce the framework for a multiresolution strategy to the problem. Registration results are presented on uoroscopy and CT datasets of a plastic pelvis and a real skull, and on a high-resolution CT- derived simulated dataset of a real skull, a plastic skull, a plastic pelvis and a plastic lumbar spine segment.

Segmentation and Alignment of Speech and Sketching in a Design Environment

Sketches are commonly used in the early stages of design. Our previous system allows users to sketch mechanical systems that the computer interprets. However, some parts of the mechanical system might be too hard or too complicated to express in the sketch. Adding speech recognition to create a multimodal system would move us toward our goal of creating a more natural user interface. This thesis examines the relationship between the verbal and sketch input, particularly how to segment and align the two inputs. Toward this end, subjects were recorded while they sketched and talked. These recordings were transcribed, and a set of rules to perform segmentation and alignment was created. These rules represent the knowledge that the computer needs to perform segmentation and alignment. The rules successfully interpreted the 24 data sets that they were given.

Pre-Attentive Segmentation in the Primary Visual Cortex

Stimuli outside classical receptive fields have been shown to exert significant influence over the activities of neurons in primary visual cortexWe propose that contextual influences are used for pre-attentive visual segmentation, in a new framework called segmentation without classification. This means that segmentation of an image into regions occurs without classification of features within a region or comparison of features between regions. This segmentation framework is simpler than previous computational approaches, making it implementable by V1 mechanisms, though higher leve l visual mechanisms are needed to refine its output. However, it easily handles a class of segmentation problems that are tricky in conventional methods. The cortex computes global region boundaries by detecting the breakdown of homogeneity or translation invariance in the input, using local intra-cortical interactions mediated by the horizontal connections. The difference between contextual influences near and far from region boundaries makes neural activities near region boundaries higher than elsewhere, making boundaries more salient for perceptual pop-out. This proposal is implemented in a biologically based model of V1, and demonstrated using examples of texture segmentation and figure-ground segregation. The model performs segmentation in exactly the same neural circuit that solves the dual problem of the enhancement of contours, as is suggested by experimental observations. Its behavior is compared with psychophysical and physiological data on segmentation, contour enhancement, and contextual influences. We discuss the implications of segmentation without classification and the predictions of our V1 model, and relate it to other phenomena such as asymmetry in visual search.

View-Based Strategies for 3D Object Recognition

A persistent issue of debate in the area of 3D object recognition concerns the nature of the experientially acquired object models in the primate visual system. One prominent proposal in this regard has expounded the use of object centered models, such as representations of the objects' 3D structures in a coordinate frame independent of the viewing parameters [Marr and Nishihara, 1978]. In contrast to this is another proposal which suggests that the viewing parameters encountered during the learning phase might be inextricably linked to subsequent performance on a recognition task [Tarr and Pinker, 1989; Poggio and Edelman, 1990]. The 'object model', according to this idea, is simply a collection of the sample views encountered during training. Given that object centered recognition strategies have the attractive feature of leading to viewpoint independence, they have garnered much of the research effort in the field of computational vision. Furthermore, since human recognition performance seems remarkably robust in the face of imaging variations [Ellis et al., 1989], it has often been implicitly assumed that the visual system employs an object centered strategy. In the present study we examine this assumption more closely. Our experimental results with a class of novel 3D structures strongly suggest the use of a view-based strategy by the human visual system even when it has the opportunity of constructing and using object-centered models. In fact, for our chosen class of objects, the results seem to support a stronger claim: 3D object recognition is 2D view-based.

3D Object Recognition: Symmetry and Virtual Views

Many 3D objects in the world around us are strongly constrained. For instance, not only cultural artifacts but also many natural objects are bilaterally symmetric. Thoretical arguments suggest and psychophysical experiments confirm that humans may be better in the recognition of symmetric objects. The hypothesis of symmetry-induced virtual views together with a network model that successfully accounts for human recognition of generic 3D objects leads to predictions that we have verified with psychophysical experiments.

Geometric and Algebraic Aspects of 3D Affine and Projective Structures from Perspective 2D Views

We investigate the differences --- conceptually and algorithmically --- between affine and projective frameworks for the tasks of visual recognition and reconstruction from perspective views. It is shown that an affine invariant exists between any view and a fixed view chosen as a reference view. This implies that for tasks for which a reference view can be chosen, such as in alignment schemes for visual recognition, projective invariants are not really necessary. We then use the affine invariant to derive new algebraic connections between perspective views. It is shown that three perspective views of an object are connected by certain algebraic functions of image coordinates alone (no structure or camera geometry needs to be involved).

Visual Segmentation without Classification in a Model of the Primary Visual Cortex

Stimuli outside classical receptive fields significantly influence the neurons' activities in primary visual cortex. We propose that such contextual influences are used to segment regions by detecting the breakdown of homogeneity or translation invariance in the input, thus computing global region boundaries using local interactions. This is implemented in a biologically based model of V1, and demonstrated in examples of texture segmentation and figure-ground segregation. By contrast with traditional approaches, segmentation occurs without classification or comparison of features within or between regions and is performed by exactly the same neural circuit responsible for the dual problem of the grouping and enhancement of contours.

Integració 3D de píxels híbrids. Més ràpid, més petit, més barat

Marc Bigas ha guanyat el premi Eduard Fonseré de ciències físiques de l'Institut d'Estudis Catalans amb la tesi Integració 3D de píxels híbrids. Bigas és, a més, responsable de desenvolupament del Parc Científic i Tecnològic de la UdG