3D Motion Analysis via Energy Minimization

This work deals with 3D motion analysis from stereo image sequences for driver assistance systems. It consists of two parts: the estimation of motion from the image data and the segmentation of moving objects in the input images. The content can be summarized with the technical term machine visual kinesthesia, the sensation or perception and cognition of motion. In the first three chapters, the importance of motion information is discussed for driver assistance systems, for machine vision in general, and for the estimation of ego motion. The next two chapters delineate on motion perception, analyzing the apparent movement of pixels in image sequences for both a monocular and binocular camera setup. Then, the obtained motion information is used to segment moving objects in the input video. Thus, one can clearly identify the thread from analyzing the input images to describing the input images by means of stationary and moving objects. Finally, I present possibilities for future applications based on the contents of this thesis. Previous work in each case is presented in the respective chapters. Although the overarching issue of motion estimation from image sequences is related to practice, there is nothing as practical as a good theory (Kurt Lewin). Several problems in computer vision are formulated as intricate energy minimization problems. In this thesis, motion analysis in image sequences is thoroughly investigated, showing that splitting an original complex problem into simplified sub-problems yields improved accuracy, increased robustness, and a clear and accessible approach to state-of-the-art motion estimation techniques. In Chapter 4, optical flow is considered. Optical flow is commonly estimated by minimizing the combined energy, consisting of a data term and a smoothness term. These two parts are decoupled, yielding a novel and iterative approach to optical flow. The derived Refinement Optical Flow framework is a clear and straight-forward approach to computing the apparent image motion vector field. Furthermore this results currently in the most accurate motion estimation techniques in literature. Much as this is an engineering approach of fine-tuning precision to the last detail, it helps to get a better insight into the problem of motion estimation. This profoundly contributes to state-of-the-art research in motion analysis, in particular facilitating the use of motion estimation in a wide range of applications. In Chapter 5, scene flow is rethought. Scene flow stands for the three-dimensional motion vector field for every image pixel, computed from a stereo image sequence. Again, decoupling of the commonly coupled approach of estimating three-dimensional position and three dimensional motion yields an approach to scene ow estimation with more accurate results and a considerably lower computational load. It results in a dense scene flow field and enables additional applications based on the dense three-dimensional motion vector field, which are to be investigated in the future. One such application is the segmentation of moving objects in an image sequence. Detecting moving objects within the scene is one of the most important features to extract in image sequences from a dynamic environment. This is presented in Chapter 6. Scene flow and the segmentation of independently moving objects are only first steps towards machine visual kinesthesia. Throughout this work, I present possible future work to improve the estimation of optical flow and scene flow. Chapter 7 additionally presents an outlook on future research for driver assistance applications. But there is much more to the full understanding of the three-dimensional dynamic scene. This work is meant to inspire the reader to think outside the box and contribute to the vision of building perceiving machines.</em

Embryological Development and Topographic Anatomy of Pelvic Compartments-Surgical Relevance for Pelvic Lymphonodectomy

Background The oncological outcome of surgery for the treatment of pelvic malignancies can be improved by performing pelvic lymphonodectomy. However, the extent and regions of lymph node harvest are debated and require profound knowledge of anatomy in order to avoid collateral damage. Methods The embryological development and topographic anatomy of pelvic compartments in relation to pelvic lymphonodectomy for rectal, uterine, and prostate cancer are reviewed. Based on pre-dissected anatomical specimens, lymph node regions and drainage routes of the posterior and urogenital pelvic compartments are described in both genders. Anatomical landmarks are highlighted to identify structures at risk of injury during pelvic lymphonodectomy. Results The ontogenesis of urogenital and anorectal compartments and their lymphatic supply are key factors for adequate lymphonodectomy, and have led to compartment-based surgical resection strategies. However, pelvic lymphonodectomy bears the risk of injury to somatic and autonomic nerves, vessels, and organs, depending on the regions and extent of surgery. Conclusion Embryologically defined, compartment-based resection of pelvic malignancies and their lymphatic drainage routes are based on clearly delineated anatomical landmarks, which permit template-oriented pelvic lymphonodectomy. Comprehensive knowledge of pelvic anatomy, the exchange of surgical concepts between specialties, and minimally invasive techniques will optimize pelvic lymphonodectomy and reduce complications

Machine-learning enabled optimization of atomic structures using atoms with fractional existence

We introduce a method for global optimization of the structure of atomic systems that uses additional atoms with fractional existence. The method allows for movement of atoms over long distances bypassing energy barriers encountered in the conventional position space. The method is based on Gaussian processes, where the extrapolation to fractional existence is performed with a vectorial fingerprint. The method is applied to clusters and two-dimensional systems, where the fractional existence variables are optimized while keeping the atomic positions fixed on a lattice. Simultaneous optimization of atomic coordinates and existence variables is demonstrated on copper clusters of varying size. The existence variables are shown to speed up the global optimization of large and particularly difficult-to-optimize clusters.Comment: 6 pages, 5 figures, plus supplemen

Exploring the constraint profile of winter sports resort tourist segments

Many studies have confirmed the importance of market segmentation both theoretically and empirically. Surprisingly though, no study has so far addressed the issue from the perspective of leisure constraints. Since different consumers face different barriers, we look at participation in leisure activities as an outcome of the negotiation process that winter sports resort tourists go through, to balance between related motives and constraints. This empirical study reports the findings on the applicability of constraining factors in segmenting the tourists who visit winter sports resorts. Utilizing data from 1,391 tourists of winter sports resorts in Greece, five segments were formed based on their constraint, demographic and behavioral profile. Our findings indicate that such segmentation sheds light on factors that could potentially limit the full utilization of the market. To maximize utilization, we suggest customizing marketing to the profile of each distinct winter sports resort tourist segment that emerge

The Amino-Terminus of Nitric Oxide Sensitive Guanylyl Cyclase α1 Does Not Affect Dimerization but Influences Subcellular Localization

BACKGROUND: Nitric oxide sensitive guanylyl cyclase (NOsGC) is a heterodimeric enzyme formed by an α- and a β₁-subunit. A splice variant (C-α₁) of the α₁-subunit, lacking at least the first 236 amino acids has been described by Sharina et al. 2008 and has been shown to be expressed in differentiating human embryonic cells. Wagner et al. 2005 have shown that the amino acids 61-128 of the α₁-subunit are mandatory for quantitative heterodimerization implying that the C-α₁-splice variant should lose its capacity to dimerize quantitatively. METHODOLOGY/PRINCIPAL FINDINGS: In the current study we demonstrate preserved quantitative dimerization of the C-α₁-splice by co-purification with the β₁-subunit. In addition we used fluorescence resonance energy transfer (FRET) based on fluorescence lifetime imaging (FLIM) using fusion proteins of the β₁-subunit and the α₁-subunit or the C-α₁ variant with ECFP or EYFP. Analysis of the respective combinations in HEK-293 cells showed that the fluorescence lifetime was significantly shorter (≈0.3 ns) for α₁/β₁ and C-α₁/β₁ than the negative control. In addition we show that lack of the amino-terminus in the α₁ splice variant directs it to a more oxidized subcellular compartment. CONCLUSIONS/SIGNIFICANCE: We conclude that the amino-terminus of the α₁-subunit is dispensable for dimerization in-vivo and ex-vivo, but influences the subcellular trafficking

GPAW: open Python package for electronic-structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE) providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe-Salpeter Equation (BSE), variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn-Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support of GPU acceleration has been achieved with minor modifications of the GPAW code thanks to the CuPy library. We end the review with an outlook describing some future plans for GPAW

Stereo Scene Flow for 3D Motion Analysis

This book presents methods for estimating optical flow and scene flow motion with high accuracy, focusing on the practical application of these methods in camera-based driver assistance systems. Clearly and logically structured, the book builds from basic themes to more advanced concepts, culminating in the development of a novel, accurate and robust optic flow method. Features: reviews the major advances in motion estimation and motion analysis, and the latest progress of dense optical flow algorithms; investigates the use of residual images for optical flow; examines methods for deriving mo