Thomas Greif

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Probabilistic models with hidden variables such as proba-bilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA) have recently become popular for solving several image content analysis tasks. In this work we will use a pLSA model to represent images for performing scene classification. We evaluate the influence of the type of local(More)
The formation of the first galaxies is influenced by the radiative feedback from the first generations of stars. This feedback is manifested by the heating and ionization of the gas which lies within the H II regions surrounding the first stars, as well as by the photodissociation of hydrogen molecules within the larger Lyman-Werner (LW) bubbles that(More)
We investigate the properties of the first galaxies at z 10 with highly resolved numerical simulations, starting from cosmological initial conditions and taking into account all relevant primordial chemistry and cooling. A first galaxy is characterized by the onset of atomic hydrogen cooling, once the virial temperature exceeds ≃ 10 4 K, and its ability to(More)
We perform three dimensional smoothed particle hydrodynamics (SPH) simulations in a realistic cosmological setting to investigate the expansion, feedback, and chemical enrichment properties of a 200 M ⊙ pair-instability supernova (PISN) in the high-redshift universe. To this end, we use the entropy-conserving formulation of the cosmological simulation code(More)
The character of the first galaxies at redshifts z > ∼ 10 strongly depends on their level of pre-enrichment, which is in turn determined by the rate of primordial star formation prior to their assembly. In order for the first galaxies to remain metal-free, star formation in minihaloes must be highly suppressed, most likely by H 2-dissociating Lyman-Werner(More)
In our previous work [4] we have shown that the representation of images by the Latent Dirichlet Allocation (LDA) model combined with an appropriate similarity measure is suitable for performing large-scale image retrieval in a real-world database. The LDA model, however, relies on the assumption that all topics are independent of each other – something(More)
We introduce a two–dimensional kinematic model for cyclic motions of humans, which is suitable for the use as temporal prior in any Bayesian tracking framework. This human motion model is solely based on simple kinematic properties: the joint accelerations. Distributions of joint accelerations subject to the cycle progress are learned from training data. We(More)
In this work we present an annotated data set for two– dimensional pose estimation of swimmers. The data set contains fifteen cycles of swimmers swimming backstroke with more than 1200 annotated video frames. A wide variety of subjects was used to create this data set, ranging from adult to teenage swimmers, both, male and female. For each frame of a cycle,(More)
In this work we propose a novel approach to automatically detect a swimmer and estimate his/her pose continuously in order to derive an estimate of his/her stroke rate given that we observe the swimmer from the side. We divide a swimming cycle of each stroke into several intervals. Each interval represents a pose of the stroke. We use specifically trained(More)
The transformation of atomic hydrogen to molecular hydrogen through three-body reactions is a crucial stage in the collapse of primordial, metal-free halos, where the first generation of stars (Population III stars) in the Universe are formed. However, in the published literature, the rate coefficient for this reaction is uncertain by nearly an order of(More)