73 research outputs found

    Die Bedeutung einer Ausfallbedrohtheit von Versicherungskontrakten - ein Beitrag zur Behavioral Insurance

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    Kahneman/Tversky 1979 haben das theoretische Konstrukt der Probabilistic Insurance Kontrakte in die Literatur eingeführt. Hiermit werden Versicherungsverträge bezeichnet, deren Erfüllung im Leistungsfalle aufgrund einer möglichen Insolvenz des Versicherungsunternehmens nicht gewährleistet ist. In Ausweitung einer Studie von Wakker/Thaler/Tversky 1997 wird in der vorliegenden Arbeit eine experimentelle Untersuchung durchgeführt, wobei die Zahlungsbereitschaft potentieller Versicherungsnehmer in Abhängigkeit des Ratings des den Versicherungskontrakt anbietenden Unternehmens festgestellt wird. Dabei zeigt sich, daß diese ausfallbedrohte Versicherungsprodukte relativ zu ausfallfreien Verträgen mit erheblichen Prämienabschlägen sanktionieren. Der Preisabschlag nimmt dabei mit sinkender Unternehmensbonität (erhöhter Ausfallgefahr) zu. Die Befragungsergebnisse zeigen zudem das neuartige Phänomen, daß mit zunehmender Ausfallbedrohtheit immer weniger Personen bereit sind, ausfallbedrohte Versicherungsprodukte überhaupt zu akzeptieren. Schließlich werden Schlußfolgerungen für die Steuerung von Versicherungsunternehmen diskutiert

    Turning aggression into an object of intervention: Tinkering in a crime control pilot study

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    Real-world experiments that test new technologies can affect policy and practice by introducing new objects of intervention through tinkering; the ad hoc work of realigning relations in the face of frictions, surprises, and disturbances that occur when introducing a technology. In a pilot study on aggression detection, tinkering moved aggression in and out of the human body. In the end, the pilot defined aggression as a set of acoustic-physical variables representing the aroused human body, alongside other signals of aggression. How aggression as an object intervention was shaped by tinkering is relevant because it involved inclusions and exclusions by the authorities who identified aggression, the methods they applied, and mandate for intervention. A focus on relations that are tinkered within a real-world experiment permits critical engagement with this format. Although the real-world experimental format is credited with producing knowledge about a technology's ‘actual’ performance, actors and events at the pilot study location were made only selectively relevant. Analyses of real-world experiments should therefore explain how experiments selectively make the world relevant, giving only particular objects of intervention a truth status

    Processing and Tracking Human Motions Using Optical, Inertial, and Depth Sensors

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    The processing of human motion data constitutes an important strand of research with many applications in computer animation, sport science and medicine. Currently, there exist various systems for recording human motion data that employ sensors of different modalities such as optical, inertial and depth sensors. Each of these sensor modalities have intrinsic advantages and disadvantages that make them suitable for capturing specific aspects of human motions as, for example, the overall course of a motion, the shape of the human body, or the kinematic properties of motions. In this thesis, we contribute with algorithms that exploit the respective strengths of these different modalities for comparing, classifying, and tracking human motion in various scenarios. First, we show how our proposed techniques can be employed, \textite.\,g., for real-time motion reconstruction using efficient cross-modal retrieval techniques. Then, we discuss a practical application of inertial sensors-based features to the classification of trampoline motions. As a further contribution, we elaborate on estimating the human body shape from depth data with applications to personalized motion tracking. Finally, we introduce methods to stabilize a depth tracker in challenging situations such as in presence of occlusions. Here, we exploit the availability of complementary inertial-based sensor information

    Full-body Human Motion Capture from Monocular Depth Images

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    Classification of Trampoline Jumps Using Inertial Sensors

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    Real-Time Body Tracking with One Depth Camera and Inertial Sensors

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    Applikationstechnische Untersuchungen im Weinbau an Pflanzenschutzgeraeten mit Einrichtungen zur Rueckfuehrung nicht angelagerter Spritzfluessigkeit

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    SIGLETIB Hannover: RA 4212(175) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

    Efficient Multi-view Performance Capture of Fine-Scale Surface Detail

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    Building Statistical Shape Spaces for {3D} Human Modeling

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    Statistical models of 3D human shape and pose learned from scan databases have developed into valuable tools to solve a variety of vision and graphics problems. Unfortunately, most publicly available models are of limited expressiveness as they were learned on very small databases that hardly reflect the true variety in human body shapes. In this paper, we contribute by rebuilding a widely used statistical body representation from the largest commercially available scan database, and making the resulting model available to the community (visit http://humanshape.mpi-inf.mpg.de). As preprocessing several thousand scans for learning the model is a challenge in itself, we contribute by developing robust best practice solutions for scan alignment that quantitatively lead to the best learned models. We make implementations of these preprocessing steps also publicly available. We extensively evaluate the improved accuracy and generality of our new model, and show its improved performance for human body reconstruction from sparse input data
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