Real-Time Dense 3D Reconstruction from Monocular Video Data Captured by Low-Cost UAVS

Real-time 3D reconstruction enables fast dense mapping of the environment which benefits numerous applications, such as navigation or live evaluation of an emergency. In contrast to most real-time capable approaches, our method does not need an explicit depth sensor. Instead, we only rely on a video stream from a camera and its intrinsic calibration. By exploiting the self-motion of the unmanned aerial vehicle (UAV) flying with oblique view around buildings, we estimate both camera trajectory and depth for selected images with enough novel content. To create a 3D model of the scene, we rely on a three-stage processing chain. First, we estimate the rough camera trajectory using a simultaneous localization and mapping (SLAM) algorithm. Once a suitable constellation is found, we estimate depth for local bundles of images using a Multi-View Stereo (MVS) approach and then fuse this depth into a global surfel-based model. For our evaluation, we use 55 video sequences with diverse settings, consisting of both synthetic and real scenes. We evaluate not only the generated reconstruction but also the intermediate products and achieve competitive results both qualitatively and quantitatively. At the same time, our method can keep up with a 30 fps video for a resolution of 768 × 448 pixels

CO2\mathrm{CO_2} exploding clusters dynamics probed by XUV fluorescence

Clusters excited by intense laser pulses are a unique source of warm dense matter, that has been the subject of intensive experimental studies. The majority of those investigations concerns atomic clusters, whereas the evolution of molecular clusters excited by intense laser pulses is less explored. In this work we trace the dynamics of $\mathrm{CO_2}$ clusters triggered by a few-cycle 1.45-$\mu$m driving pulse through the detection of XUV fluorescence induced by a delayed 800-nm ignition pulse. Striking differences among fluorescence dynamics from different ionic species are observed

DEEP CROSS-DOMAIN BUILDING EXTRACTION FOR SELECTIVE DEPTH ESTIMATION FROM OBLIQUE AERIAL IMAGERY

With the technological advancements of aerial imagery and accurate 3d reconstruction of urban environments, more and more attention has been paid to the automated analyses of urban areas. In our work, we examine two important aspects that allow online analysis of building structures in city models given oblique aerial image sequences, namely automatic building extraction with convolutional neural networks (CNNs) and selective real-time depth estimation from aerial imagery. We use transfer learning to train the Faster R-CNN method for real-time deep object detection, by combining a large ground-based dataset for urban scene understanding with a smaller number of images from an aerial dataset. We achieve an average precision (AP) of about 80 % for the task of building extraction on a selected evaluation dataset. Our evaluation focuses on both dataset-specific learning and transfer learning. Furthermore, we present an algorithm that allows for multi-view depth estimation from aerial image sequences in real-time. We adopt the semi-global matching (SGM) optimization strategy to preserve sharp edges at object boundaries. In combination with the Faster R-CNN, it allows a selective reconstruction of buildings, identified with regions of interest (RoIs), from oblique aerial imagery

ReS²tAC—UAV-borne real-time SGM stereo optimized for embedded ARM and CUDA devices

With the emergence of low-cost robotic systems, such as unmanned aerial vehicle, the importance of embedded high-performance image processing has increased. For a long time, FPGAs were the only processing hardware that were capable of high-performance computing, while at the same time preserving a low power consumption, essential for embedded systems. However, the recently increasing availability of embedded GPU-based systems, such as the NVIDIA Jetson series, comprised of an ARM CPU and a NVIDIA Tegra GPU, allows for massively parallel embedded computing on graphics hardware. With this in mind, we propose an approach for real-time embedded stereo processing on ARM and CUDA-enabled devices, which is based on the popular and widely used Semi-Global Matching algorithm. In this, we propose an optimization of the algorithm for embedded CUDA GPUs, by using massively parallel computing, as well as using the NEON intrinsics to optimize the algorithm for vectorized SIMD processing on embedded ARM CPUs. We have evaluated our approach with different configurations on two public stereo benchmark datasets to demonstrate that they can reach an error rate as low as 3.3%. Furthermore, our experiments show that the fastest configuration of our approach reaches up to 46 FPS on VGA image resolution. Finally, in a use-case specific qualitative evaluation, we have evaluated the power consumption of our approach and deployed it on the DJI Manifold 2-G attached to a DJI Matrix 210v2 RTK unmanned aerial vehicle (UAV), demonstrating its suitability for real-time stereo processing onboard a UAV

Critical sets of nonlinear Sturm-Liouville operators of Ambrosetti-Prodi type

The critical set C of the operator F:H^2_D([0,pi]) -> L^2([0,pi]) defined by F(u)=-u''+f(u) is studied. Here X:=H^2_D([0,pi]) stands for the set of functions that satisfy the Dirichlet boundary conditions and whose derivatives are in L^2([0,pi]). For generic nonlinearities f, C=\cup C_k decomposes into manifolds of codimension 1 in X. If f''0, the set C_j is shown to be non-empty if, and only if, -j^2 (the j-th eigenvalue of u -> u'') is in the range of f'. The critical components C_k are (topological) hyperplanes.Comment: 6 pages, no figure

Proposal to Search for Heavy Neutral Leptons at the SPS

A new fixed-target experiment at the CERN SPS accelerator is proposed that will use decays of charm mesons to search for Heavy Neutral Leptons (HNLs), which are right-handed partners of the Standard Model neutrinos. The existence of such particles is strongly motivated by theory, as they can simultaneously explain the baryon asymmetry of the Universe, account for the pattern of neutrino masses and oscillations and provide a Dark Matter candidate. Cosmological constraints on the properties of HNLs now indicate that the majority of the interesting parameter space for such particles was beyond the reach of the previous searches at the PS191, BEBC, CHARM, CCFR and NuTeV experiments. For HNLs with mass below 2 GeV, the proposed experiment will improve on the sensitivity of previous searches by four orders of magnitude and will cover a major fraction of the parameter space favoured by theoretical models. The experiment requires a 400 GeV proton beam from the SPS with a total of 2x10^20 protons on target, achievable within five years of data taking. The proposed detector will reconstruct exclusive HNL decays and measure the HNL mass. The apparatus is based on existing technologies and consists of a target, a hadron absorber, a muon shield, a decay volume and two magnetic spectrometers, each of which has a 0.5 Tm magnet, a calorimeter and a muon detector. The detector has a total length of about 100 m with a 5 m diameter. The complete experimental set-up could be accommodated in CERN's North Area. The discovery of a HNL would have a great impact on our understanding of nature and open a new area for future research

Bubble concentration on spheres for supercritical elliptic problems

We consider the supercritical Lane-Emden problem (P_\eps)\qquad -\Delta v= |v|^{p_\eps-1} v \ \hbox{in}\ \mathcal{A} ,\quad u=0\ \hbox{on}\ \partial\mathcal{A} where $\mathcal A$ is an annulus in \rr^{2m}, $m\ge2$ and p_\eps={(m+1)+2\over(m+1)-2}-\eps, \eps>0. We prove the existence of positive and sign changing solutions of (P_\eps) concentrating and blowing-up, as \eps\to0, on $(m-1)-$dimensional spheres. Using a reduction method (see Ruf-Srikanth (2010) J. Eur. Math. Soc. and Pacella-Srikanth (2012) arXiv:1210.0782)we transform problem (P_\eps) into a nonhomogeneous problem in an annulus \mathcal D\subset \rr^{m+1} which can be solved by a Ljapunov-Schmidt finite dimensional reduction

Pair production in laser fields oscillating in space and time

The production of electron-positron pairs from vacuum by counterpropagating laser beams of linear polarization is calculated. In contrast to the usual approximate approach, the spatial dependence and magnetic component of the laser field are taken into account. We show that the latter strongly affects the creation process at high laser frequency: the production probability is reduced, the kinematics is fundamentally modified, the resonant Rabi-oscillation pattern is distorted and the resonance positions are shifted, multiplied and split.Comment: 5 pages, 5 figure

A Reversible Gene-Targeting Strategy Identifies Synthetic Lethal Interactions between MK2 and p53 in the DNA Damage Response In Vivo

A fundamental limitation in devising new therapeutic strategies for killing cancer cells with DNA damaging agents is the need to identify synthetic lethal interactions between tumor-specific mutations and components of the DNA damage response (DDR) in vivo. The stress-activated p38 mitogen-activated protein kinase (MAPK)/MAPKAP kinase-2 (MK2) pathway is a critical component of the DDR network in p53-deficient tumor cells in vitro. To explore the relevance of this pathway for cancer therapy in vivo, we developed a specific gene targeting strategy in which Cre-mediated recombination simultaneously creates isogenic MK2-proficient and MK2-deficient tumors within a single animal. This allows direct identification of MK2 synthetic lethality with mutations that promote tumor development or control response to genotoxic treatment. In an autochthonous model of non-small-cell lung cancer (NSCLC), we demonstrate that MK2 is responsible for resistance of p53-deficient tumors to cisplatin, indicating synthetic lethality between p53 and MK2 can successfully be exploited for enhanced sensitization of tumors to DNA-damaging chemotherapeutics in vivo.National Institutes of Health (U.S.) (Grant ES015339)National Institutes of Health (U.S.) (Grant GM60594)National Institutes of Health (U.S.) (Grant GM59281)National Institutes of Health (U.S.) (Grant CA112967)Janssen Pharmaceutical Ltd.Massachusetts Institute of Technology. Center for Environmental Health Sciences (Core Grant P30-CA14051)Massachusetts Institute of Technology. Center for Environmental Health Sciences (Core Grant ES-002109