160 research outputs found

    A Multi-body Tracking Framework -- From Rigid Objects to Kinematic Structures

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    Kinematic structures are very common in the real world. They range from simple articulated objects to complex mechanical systems. However, despite their relevance, most model-based 3D tracking methods only consider rigid objects. To overcome this limitation, we propose a flexible framework that allows the extension of existing 6DoF algorithms to kinematic structures. Our approach focuses on methods that employ Newton-like optimization techniques, which are widely used in object tracking. The framework considers both tree-like and closed kinematic structures and allows a flexible configuration of joints and constraints. To project equations from individual rigid bodies to a multi-body system, Jacobians are used. For closed kinematic chains, a novel formulation that features Lagrange multipliers is developed. In a detailed mathematical proof, we show that our constraint formulation leads to an exact kinematic solution and converges in a single iteration. Based on the proposed framework, we extend ICG, which is a state-of-the-art rigid object tracking algorithm, to multi-body tracking. For the evaluation, we create a highly-realistic synthetic dataset that features a large number of sequences and various robots. Based on this dataset, we conduct a wide variety of experiments that demonstrate the excellent performance of the developed framework and our multi-body tracker.Comment: Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligenc

    6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics

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    We present a novel technique to estimate the 6D pose of objects from single images where the 3D geometry of the object is only given approximately and not as a precise 3D model. To achieve this, we employ a dense 2D-to-3D correspondence predictor that regresses 3D model coordinates for every pixel. In addition to the 3D coordinates, our model also estimates the pixel-wise coordinate error to discard correspondences that are likely wrong. This allows us to generate multiple 6D pose hypotheses of the object, which we then refine iteratively using a highly efficient region-based approach. We also introduce a novel pixel-wise posterior formulation by which we can estimate the probability for each hypothesis and select the most likely one. As we show in experiments, our approach is capable of dealing with extreme visual conditions including overexposure, high contrast, or low signal-to-noise ratio. This makes it a powerful technique for the particularly challenging task of estimating the pose of tumbling satellites for in-orbit robotic applications. Our method achieves state-of-the-art performance on the SPEED+ dataset and has won the SPEC2021 post-mortem competition.Comment: preprin

    The influence of bicuspid aortic valves on the dynamic pressure distribution in the ascending aorta: a porcine ex vivo model †

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    OBJECTIVES The aim of the study was to simulate the effect of different bicuspid aortic valve configurations on the dynamic pressure distribution in the ascending aorta. METHODS Aortic specimens were harvested from adult domestic pigs. In Group 1, bicuspidalization was created by a running suture between the left and the right coronary leaflets (n = 6) and in Group 2 by a running suture between the left and the non-coronary leaflets (n = 6). Eleven tricuspid specimens served as controls. Two intraluminal pressure catheters were positioned at the concavity and the convexity of the ascending aorta. The specimens were connected to a mock circulation (heart rate: 60 bpm, target pressure: 95 mmHg). A comparison of the different conditions was also done in a numerical simulation. RESULTS At a distal mean aortic pressure of 94 ± 10 mmHg, a mean flow rate of 5.2 ± 0.3 l/min was achieved. The difference of maximal dynamic pressure values (which occurred in systole) between locations at the convexity and the concavity was 7.8 ± 2.9 mmHg for the bicuspid and 1.0 ± 0.9 mmHg for the tricuspid specimens (P < 0.001). The numerical simulation revealed an even higher pressure difference between convexity and concavity for bicuspid formation. CONCLUSIONS In this hydrodynamic mock circulation model, we were able to demonstrate that bicuspid aortic valves are associated with significant pressure differences in different locations within the ascending aorta compared with tricuspid aortic valves. These altered pressure distributions and flow patterns may further add to the understanding of aneurismal development in patients with bicuspid aortic valves and might serve to anticipate adverse aortic events due to a better knowledge of the underlying mechanism

    Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects

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    Tracking objects in 3D space and predicting their 6DoF pose is an essential task in computer vision. State-of-the-art approaches often rely on object texture to tackle this problem. However, while they achieve impressive results, many objects do not contain sufficient texture, violating the main underlying assumption. In the following, we thus propose ICG, a novel probabilistic tracker that fuses region and depth information and only requires the object geometry. Our method deploys correspondence lines and points to iteratively refine the pose. We also implement robust occlusion handling to improve performance in real-world settings. Experiments on the YCB-Video, OPT, and Choi datasets demonstrate that, even for textured objects, our approach outperforms the current state of the art with respect to accuracy and robustness. At the same time, ICG shows fast convergence and outstanding efficiency, requiring only 1.3 ms per frame on a single CPU core. Finally, we analyze the influence of individual components and discuss our performance compared to deep learning-based methods. The source code of our tracker is publicly available

    SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World

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    Region-based methods have become increasingly popular for model-based, monocular 3D tracking of texture-less objects in cluttered scenes. However, while they achieve state-of-the-art results, most methods are computationally expensive, requiring significant resources to run in real-time. In the following, we build on our previous work and develop SRT3D, a sparse region-based approach to 3D object tracking that bridges this gap in efficiency. Our method considers image information sparsely along so-called correspondence lines that model the probability of the object's contour location. We thereby improve on the current state of the art and introduce smoothed step functions that consider a defined global and local uncertainty. For the resulting probabilistic formulation, a thorough analysis is provided. Finally, we use a pre-rendered sparse viewpoint model to create a joint posterior probability for the object pose. The function is maximized using second-order Newton optimization with Tikhonov regularization. During the pose estimation, we differentiate between global and local optimization, using a novel approximation for the first-order derivative employed in the Newton method. In multiple experiments, we demonstrate that the resulting algorithm improves the current state of the art both in terms of runtime and quality, performing particularly well for noisy and cluttered images encountered in the real world

    Agile Entwicklung physischer Produkte 2023: Eine Studie zum aktuellen Stand in der industriellen Praxis

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    In der Entwicklung von mechatronischen Produkten nimmt die agile Entwicklung bereits seit einigen Jahren eine zunehmend wichtigere Rolle ein. Im Rahmen dieser Studienserie wird seit 2018 das Fortschreiten der Agilität in der DACH-Region untersucht. In der vorliegenden Ausgabe des Jahres 2023 liegt der Fokus dem Verständnis und der Anwendung agiler Arbeitsweisen, den Herausforderungen in deren Skalierung und der Bedeutung von Prototyping im genannten Kontext. Die Ergebnisse dieser Studie beruhen, wie auch in den vorangegangenen Jahren, auf den Aussagen von Praktikern aus einem breiten Spektrum an Industrieunternehmen, die an einer Online-Umfrage teilgenommen haben. Die Studie beschreibt sowohl quantitative als auch qualitative Ergebnisse aus der industriellen Praxis

    Complement-Mediated Virus Infectivity Neutralisation by HLA Antibodies Is Associated with Sterilising Immunity to SIV Challenge in the Macaque Model for HIV/AIDS.

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    Sterilising immunity is a desired outcome for vaccination against human immunodeficiency virus (HIV) and has been observed in the macaque model using inactivated simian immunodeficiency virus (SIV). This protection was attributed to antibodies specific for cell proteins including human leucocyte antigens (HLA) class I and II incorporated into virions during vaccine and challenge virus preparation. We show here, using HLA bead arrays, that vaccinated macaques protected from virus challenge had higher serum antibody reactivity compared with non-protected animals. Moreover, reactivity was shown to be directed against HLA framework determinants. Previous studies failed to correlate serum antibody mediated virus neutralisation with protection and were confounded by cytotoxic effects. Using a virus entry assay based on TZM-bl cells we now report that, in the presence of complement, serum antibody titres that neutralise virus infectivity were higher in protected animals. We propose that complement-augmented virus neutralisation is a key factor in inducing sterilising immunity and may be difficult to achieve with HIV/SIV Env-based vaccines. Understanding how to overcome the apparent block of inactivated SIV vaccines to elicit anti-envelope protein antibodies that effectively engage the complement system could enable novel anti-HIV antibody vaccines that induce potent, virolytic serological response to be developed

    The AP-1-BATF and -BATF3 module is essential for growth, survival and TH17/ILC3 skewing of anaplastic large cell lymphoma.

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    Transcription factor AP-1 is constitutively activated and IRF4 drives growth and survival in ALK+ and ALK- anaplastic large cell lymphoma (ALCL). Here we demonstrate high-level BATF and BATF3 expression in ALCL. Both BATFs bind classical AP-1 motifs and interact with in ALCL deregulated AP-1 factors. Together with IRF4, they co-occupy AP-1-IRF composite elements, differentiating ALCL from non-ALCL. Gene-specific inactivation of BATFs, or global AP-1 inhibition results in ALCL growth retardation and/or cell death in vitro and in vivo. Furthermore, the AP-1-BATF module establishes TH17/group 3 innate lymphoid cells (ILC3)-associated gene expression in ALCL cells, including marker genes such as AHR, IL17F, IL22, IL26, IL23R and RORγt. Elevated IL-17A and IL-17F levels were detected in a subset of children and adolescents with ALK+ ALCL. Furthermore, a comprehensive analysis of primary lymphoma data confirms TH17-, and in particular ILC3-skewing in ALCL compared with PTCL. Finally, pharmacological inhibition of RORC as single treatment leads to cell death in ALCL cell lines and, in combination with the ALK inhibitor crizotinib, enforces death induction in ALK+ ALCL. Our data highlight the crucial role of AP-1/BATFs in ALCL and lead to the concept that some ALCL might originate from ILC3
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