291 research outputs found
F. V. Habermann: Philomela pia, sive missae sex
No full textThis bachelor thesis deals with the mass cycle Philomela pia by František Václav Habermann (1706-1783), a composer being nowadays mentioned primarily in connection with G. F. Handel, who used some of Habermann's music fragments in his own works. The paper summarizes the present knowledge of Habermann's biography and works, listing all the source materials of this mass cycle as well, but the central focus is on two analytical chapters. The first of them attempts to cover the basic parameters of Habermann's masses and puts them to the Central European as well as Italian musical context, the second one contains a detailed study of the technique and the extent of Handel's reworkings of Habermann's music, together with a comparison of the compositional techniques of both composers. An edition of five masses from the cycle is included. Key Words F. V. Habermann, Philomela pia, mass compositions, concertato mass, 18th century, G. F. Handel, Jephtha, borrowings, music analysi
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Marc-Antoine Charpentier's Messe pour Monsieur Mauroy
No full textMarc-Antoine Charpentier's setting of the Messe pour Monsieur Mauroy is the only composition in his oeuvre which was dedicated to a particular person. Each of Charpentier's twelve mass settings is unique; this mass setting is his longest at over 1,500 measures. Charpentier masses are diverse: one composition for women's voices, a mass for instruments only, a Christmas mass, as well as settings of the Requiem text. This document traces the history of the missa concertata up until the time of Charpentier. It examines the intricacies of Charpentier's compositional process: form, melody, harmony, and self-borrowing. This paper also analyzes recent findings as to the pronunciation of Latin in France during this time period. It also explores the correlations between the Mass and oration - the understanding and implementation of rhetoric. Musical examples from the Mass, period treatises, and phonetic transcriptions of French-Latin are a part of this document.</p
Proteinexpressionsmuster von Thrombozyten gesunder Proband/innen und Patienten/innen mit kolorektalen Karzinomen im Früh- und Spätstadium
No full textReal-time human performance capture and synthesis
No full textMost of the images one finds in the media, such as on the Internet or in textbooks and magazines, contain humans as the main point of attention. Thus, there is an inherent necessity for industry, society, and private persons to be able to thoroughly analyze and synthesize the human-related content in these images. One aspect of this analysis and subject of this thesis is to infer the 3D pose and surface deformation, using only visual information, which is also known as human performance capture. Human performance capture enables the tracking of virtual characters from real-world observations, and this is key for visual effects, games, VR, and AR, to name just a few application areas. However, traditional capture methods usually rely on expensive multi-view (marker-based) systems that are prohibitively expensive for the vast majority of people, or they use depth sensors, which are still not as common as single color cameras. Recently, some approaches have attempted to solve the task by assuming only a single RGB image is given. Nonetheless, they can either not track the dense deforming geometry of the human, such as the clothing layers, or they are far from real time, which is indispensable for many applications. To overcome these shortcomings, this thesis proposes two monocular human performance capture methods, which for the first time allow the real-time capture of the dense deforming geometry as well as an unseen 3D accuracy for pose and surface deformations. At the technical core, this work introduces novel GPU-based and data-parallel optimization strategies in conjunction with other algorithmic design choices that are all geared towards real-time performance at high accuracy. Moreover, this thesis presents a new weakly supervised multiview training strategy combined with a fully differentiable character representation that shows superior 3D accuracy. However, there is more to human-related Computer Vision than only the analysis of people in images. It is equally important to synthesize new images of humans in unseen poses and also from camera viewpoints that have not been observed in the real world. Such tools are essential for the movie industry because they, for example, allow the synthesis of photo-realistic virtual worlds with real-looking humans or of contents that are too dangerous for actors to perform on set. But also video conferencing and telepresence applications can benefit from photo-real 3D characters, as they can enhance the immersive experience of these applications. Here, the traditional Computer Graphics pipeline for rendering photo-realistic images involves many tedious and time-consuming steps that require expert knowledge and are far from real time. Traditional rendering involves character rigging and skinning, the modeling of the surface appearance properties, and physically based ray tracing. Recent learning-based methods attempt to simplify the traditional rendering pipeline and instead learn the rendering function from data resulting in methods that are easier accessible to non-experts. However, most of them model the synthesis task entirely in image space such that 3D consistency cannot be achieved, and/or they fail to model motion- and view-dependent appearance effects. To this end, this thesis presents a method and ongoing work on character synthesis, which allow the synthesis of controllable photoreal characters that achieve motion- and view-dependent appearance effects as well as 3D consistency and which run in real time. This is technically achieved by a novel coarse-to-fine geometric character representation for efficient synthesis, which can be solely supervised on multi-view imagery. Furthermore, this work shows how such a geometric representation can be combined with an implicit surface representation to boost synthesis and geometric quality
Risk Sharing and Efficiency Implications of Progressive Pension Arrangements
No full textThe present paper aims to quantify the welfare effects of progressive pension arrangements in Germany. Starting from a purely contribution-related benefit system, we introduce basic allowances for contributions and a flat benefit fraction. Since our overlapping-generations model takes into account variable labor supply, borrowing constraints as well as stochastic income risk, we can compare the labor supply, the liquidity, and the insurance effects of the policy reform. Our simulations indicate that for a realistic parameter combination an increase in pension progressivity would yield an aggregate efficiency gain of more than 2 percent of resources. However, such a reform would not be implemented because it would not find political support of the currently living generations.pension reform, idiosyncratic labor income uncertainty
Modeling Efficient Deep Representations for Human Digitization with Affordable Setup
No full textA Digital human is a photorealistic 3D human model. Digital humans have a wide range of potential applications. For example, they can be used in free-viewpoint videos that allow users to freely choose the viewpoint position and orientation. Additionally, digital humans can be used in telepresence, where people in different locations can feel as though they are in the same space. Furthermore, we can enable more immersive virtual meetings than traditional videoconferencing software such as Zoom. In current systems, to create a digital human, we need to first capture the subject using a dense array of cameras, and apply multi-view stereo algorithm to obtain the 3D scan. Next, a 3D artist should clean up the 3D scan, rig, and animate it. Lastly, lighting and rendering are performed to create the video of a digital human. Those procedures require expensive hardware setups. Also, they are very complicated, time-consuming, and need to be performed in very specialized and constrained environments. This means that the current system of creating digital humans is not affordable to everyone. Enabling affordable human digitization can facilitate broader access to immersive digital experiences. Therefore, this thesis aims to model an efficient representation that can reconstruct a 3D human with an affordable setup. To this end, this thesis makes efforts from two different and important aspects: human performance capture and avatar synthesis. Human performance capture is the process of capturing and reproducing the movements, postures, appearances, and facial expressions of human performers in digital form. Avatar synthesis is the process of synthesizing the human subject in new poses. For human performance capture, this thesis mainly works on achieving identity generalization from sparse camera inputs.The goal here is to create a representation that can synthesize the novel view of an unseen human subject using just a few sparse multi-view inputs. This direction is especially important to realize the immersive AR and VR experience where we need to instantly capture and reconstruct the changing appearance of the subject. This thesis first explores volumetric representation to achieve generalization. Here, we enhance image synthesis quality as well as temporal coherency by leveraging complementary information between different time frames. Second, this thesis presents neural radiance fields conditioned on a parametric human template. Human performance capture of an arbitrary human at inference time is highly challenging due to the heavy occlusions and dynamic articulations of the body parts. By leveraging the human prior, we achieve robust performance. We further improved the rendering quality as well as the cross-dataset generalizability by incorporating image-based rendering. For affordable avatar synthesis, this thesis presents an animatable representation that can be learned solely from the RGB video sequences. Specifically, this work proposes a two-surface parameterized light field that can synthesize the subject in new poses with high quality in real time. Finally, this thesis presents the practical application of our 3D human digitization methods in the domain of telemedicine. To demonstrate this, the proposed human performance capture methods are applied to a dataset that records a patient with Parkinson's disease. The results illustrate that our method can synthesize plausible novel views using sparse camera inputs. This highlights the potential of our human digitization methods to further expand the field of telemedicine.Doctor of Philosoph
Regarding pathogenesis of middle ear cholesteatoma
No full textУ роботі автор дійшов висновку, що розвиток холестеатоми середнього вуха при хронічному
гнійному середньому отиті є результатом порушення нормальних процесів загоєння в кістковій рані.
Дотримуючись концепції Habermann, він вважає, що розвиток холестеатоми в середньому вусі
пов’язане з атипичним запальним розростанням вростаючого в середнє вухо епидермиса зовнішнього
слухового проходуThe author concludes in his work that cholesteatoma development in the middle ear at chronic otopyosis
media results from bony-wound reparation disorders. Following Habermann’s conception, the author suggests
that cholesteatoma development in the middle ear is linked to atypical inflammatory in-growth of the external
auditory canal epidermis into the middle ear cavity
Regarding pathogenesis of middle ear cholesteatoma
No full textУ роботі автор дійшов висновку, що розвиток холестеатоми середнього вуха при хронічному
гнійному середньому отиті є результатом порушення нормальних процесів загоєння в кістковій рані.
Дотримуючись концепції Habermann, він вважає, що розвиток холестеатоми в середньому вусі
пов’язане з атипичним запальним розростанням вростаючого в середнє вухо епидермиса зовнішнього
слухового проходуThe author concludes in his work that cholesteatoma development in the middle ear at chronic otopyosis
media results from bony-wound reparation disorders. Following Habermann’s conception, the author suggests
that cholesteatoma development in the middle ear is linked to atypical inflammatory in-growth of the external
auditory canal epidermis into the middle ear cavity
Real-time Human Performance Capture and Synthesis
No full textMost of the images one finds in the media, such as on the Internet or in textbooks and magazines, contain humans as the main point of attention. Thus, there is an inherent necessity for industry, society, and private persons to be able to thoroughly analyze and synthesize the human-related content in these images. One aspect of this analysis and subject of this thesis is to infer the 3D pose and surface deformation, using only visual information, which is also known as human performance capture. Human performance capture enables the tracking of virtual characters from real-world observations, and this is key for visual effects, games, VR, and AR, to name just a few application areas. However, traditional capture methods usually rely on expensive multi-view (marker-based) systems that are prohibitively expensive for the vast majority of people, or they use depth sensors, which are still not as common as single color cameras. Recently, some approaches have attempted to solve the task by assuming only a single RGB image is given. Nonetheless, they can either not track the dense deforming geometry of the human, such as the clothing layers, or they are far from real time, which is indispensable for many applications. To overcome these shortcomings, this thesis proposes two monocular human performance capture methods, which for the first time allow the real-time capture of the dense deforming geometry as well as an unseen 3D accuracy for pose and surface deformations. At the technical core, this work introduces novel GPU-based and data-parallel optimization strategies in conjunction with other algorithmic design choices that are all geared towards real-time performance at high accuracy. Moreover, this thesis presents a new weakly supervised multiview training strategy combined with a fully differentiable character representation that shows superior 3D accuracy. However, there is more to human-related Computer Vision than only the analysis of people in images. It is equally important to synthesize new images of humans in unseen poses and also from camera viewpoints that have not been observed in the real world. Such tools are essential for the movie industry because they, for example, allow the synthesis of photo-realistic virtual worlds with real-looking humans or of contents that are too dangerous for actors to perform on set. But also video conferencing and telepresence applications can benefit from photo-real 3D characters, as they can enhance the immersive experience of these applications. Here, the traditional Computer Graphics pipeline for rendering photo-realistic images involves many tedious and time-consuming steps that require expert knowledge and are far from real time. Traditional rendering involves character rigging and skinning, the modeling of the surface appearance properties, and physically based ray tracing. Recent learning-based methods attempt to simplify the traditional rendering pipeline and instead learn the rendering function from data resulting in methods that are easier accessible to non-experts. However, most of them model the synthesis task entirely in image space such that 3D consistency cannot be achieved, and/or they fail to model motion- and view-dependent appearance effects. To this end, this thesis presents a method and ongoing work on character synthesis, which allow the synthesis of controllable photoreal characters that achieve motion- and view-dependent appearance effects as well as 3D consistency and which run in real time. This is technically achieved by a novel coarse-to-fine geometric character representation for efficient synthesis, which can be solely supervised on multi-view imagery. Furthermore, this work shows how such a geometric representation can be combined with an implicit surface representation to boost synthesis and geometric quality.ERC Consolidator Grant 4DRepLy (770784)EG Graphics Dissertation Onlin
2010-2011 Philharmonia Season Program
No full textPhilharmonia No. 1 October 9, 2010 at 7:30 PM and October 10, 2010 at 4:00 PM Albert-George Schram, music director and conductor ; Elmar Oliveira, violin Feierlicher Einzug der Ritter des Johanniterordens / Richard Strauss, arranged by Karl Kramer -- Violin Concerto in E Minor, op. 64 / Felix Mendelssohn -- Symphony No. 5 in C-sharp Minor / Gustav Mahler
Philharmonia No. 2 November 6, 2010 at 7:30 PM and November 7, 2010 at 4:00 PM Albert-George Schram, music director and conductor ; Tao Lin, piano Overture to Ruslan and Lyudmila / Mikhail Glinka -- Piano Concerto No. 25 in C Major, K. 503 / Wolfgang Amadeus Mozart -- Symphohy No. 2 in D Major, op. 43 / Jean Sibelius
Philharmonia No. 3 December 4, 2010 at 7:30 PM and December 5, 2010 at 4:00 PM Concerto Competition Winners
Philharmonia No. 4 January 29, 2011 at 7:30 PM and January 30, 2011 at 4:00 PM Gunther Schuller, guest conductor ; Lisa Leonard, piano ; Marc Reese, trumpet Die Vorstellung des Chaos from Die Schöpfung (The Representation of Chaos from the Creation) / Joseph Haydn -- Concerto for Piano, Trumpet and Strings in C Minor, op. 35 / Dmitri Shostakovich -- Symphony No. 3 in F Major, op. 90 / Johannes Brahms
Philharmonia No. 5 February 19, 2011 at 7:30 PM and February 20, 2011 at 4:00 PM Jon Robertson, guest conductor ; Roberta Rust, piano Piano Concerto No. 5 in E-flat Major, op. 73 ( Emperor ) / Ludwig van Beethoven -- Symphony No. 6 in D Major, op. 60 / Antonín Dvořák
Philharmonia No. 6 March 26, 2011 at 7:30 PM and March 27, 2011 at 4:00 PM Albert-George Schram, music director ; Amanda Hall, soprano ; Christin-Marie Hill, mezzo-soprano ; Scott Ramsey, tenor ; Wayne Shepperd, bass-baritone ; Joshua Habermann, Master Chorale of South Florida artistic director and conductor ; Master Chorale of South Florida Messa da Requiem / Giusepe Verdihttps://spiral.lynn.edu/conservatory_philharmonia/1022/thumbnail.jp
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