Fast Recognition of Partial Star Products and Quasi Cartesian Products

This paper is concerned with the fast computation of a relation $\R$ on the edge set of connected graphs that plays a decisive role in the recognition of approximate Cartesian products, the weak reconstruction of Cartesian products, and the recognition of Cartesian graph bundles with a triangle free basis. A special case of $\R$ is the relation $\delta^\ast$, whose convex closure yields the product relation $\sigma$ that induces the prime factor decomposition of connected graphs with respect to the Cartesian product. For the construction of $\R$ so-called Partial Star Products are of particular interest. Several special data structures are used that allow to compute Partial Star Products in constant time. These computations are tuned to the recognition of approximate graph products, but also lead to a linear time algorithm for the computation of $\delta^\ast$ for graphs with maximum bounded degree. Furthermore, we define \emph{quasi Cartesian products} as graphs with non-trivial $\delta^\ast$. We provide several examples, and show that quasi Cartesian products can be recognized in linear time for graphs with bounded maximum degree. Finally, we note that quasi products can be recognized in sublinear time with a parallelized algorithm

D2-Net: A Trainable CNN for Joint Detection and Description of Local Features

In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions. We propose an approach where a single convolutional neural network plays a dual role: It is simultaneously a dense feature descriptor and a feature detector. By postponing the detection to a later stage, the obtained keypoints are more stable than their traditional counterparts based on early detection of low-level structures. We show that this model can be trained using pixel correspondences extracted from readily available large-scale SfM reconstructions, without any further annotations. The proposed method obtains state-of-the-art performance on both the difficult Aachen Day-Night localization dataset and the InLoc indoor localization benchmark, as well as competitive performance on other benchmarks for image matching and 3D reconstruction.Comment: Accepted at CVPR 201

The when, where, and how: an adaptive robotic info-terminal for care home residents – a long-term study

Adapting to users' intentions is a key requirement for autonomous robots in general, and in care settings in particular. In this paper, a comprehensive long-term study of a mobile robot providing information services to residents, visitors, and staff of a care home is presented with a focus on adapting to the when and where the robot should be offering its services to best accommodate the users' needs. Rather than providing a fixed schedule, the presented system takes the opportunity of long-term deployment to explore the space of possibilities of interaction while concurrently exploiting the model learned to provide better services. But in order to provide effective services to users in a care home, not only then when and where are relevant, but also the way how the information is provided and accessed. Hence, also the usability of the deployed system is studied specifically, in order to provide a most comprehensive overall assessment of a robotic info-terminal implementation in a care setting. Our results back our hypotheses, (i) that learning a spatiotemporal model of users' intentions improves efficiency and usefulness of the system, and (ii) that the specific information sought after is indeed dependent on the location the info-terminal is offered

Self-consistent theory of current injection into d and d plus is superconductors

We present results for the steady-state nonlinear response of a dx2-y2 Delta s <i . The resulting spectral rearrangements and voltage-dependent scattering amplitudes lead to a pronounced non-thermally broadened split of the zero-bias conductance peak that is not seen in a non-selfconsistent Landauer-Buttiker scattering approach

InLoc: Indoor Visual Localization with Dense Matching and View Synthesis

We seek to predict the 6 degree-of-freedom (6DoF) pose of a query photograph with respect to a large indoor 3D map. The contributions of this work are three-fold. First, we develop a new large-scale visual localization method targeted for indoor environments. The method proceeds along three steps: (i) efficient retrieval of candidate poses that ensures scalability to large-scale environments, (ii) pose estimation using dense matching rather than local features to deal with textureless indoor scenes, and (iii) pose verification by virtual view synthesis to cope with significant changes in viewpoint, scene layout, and occluders. Second, we collect a new dataset with reference 6DoF poses for large-scale indoor localization. Query photographs are captured by mobile phones at a different time than the reference 3D map, thus presenting a realistic indoor localization scenario. Third, we demonstrate that our method significantly outperforms current state-of-the-art indoor localization approaches on this new challenging data

Growth Rate Effects on Temporal Trajectories of Ring Width, Wood Density, and Mean Tracheid Length in Norway Spruce (Picea Abies (L.) Karst.)

The study reported was conducted on 20 fast-grown and 20 slow-grown Norway spruces (Picea abies (L.) Karst.) from an even-aged, plantation-grown stand near Rendeux, Belgian Ardennes. The objective was to test whether increasing the growth rate of Norway spruce by heavy thinnings had an effect on the temporal trajectories (i.e., fluctuations from year to year) of ring width, wood density, and mean tracheid length, all measured yearly from pith to bark. Since the data were chronologies (i.e., time series of yearly measurements), time had to be considered as a factor (i.e., the calendar year of ring formation) in the statistical analysis of the within-tree variation (repeated measures analysis of variance).While the effects of the growth category and its interaction with the year were highly significant after first thinning for ring width, a significant decrease in the wood density of fast-grown trees was observed in many years during that growing period; the decrease was small in magnitude, once averaged over years (-0.033 g/cm3). Tracheids were longer for the slow-grown trees after first thinning; although constant in sign and magnitude over years, the difference in mean tracheid length between growth categories was not statistically significant. In summary, increasing the growth rate in circumference of Norway spruce from 1.7 to 2.7 cm/year by heavy thinnings induced a limited decrease in wood density and mean tracheid length. These results support the statement that stand productivity might be improved without sensible loss of wood quality

Thermopower and thermophase in a d -wave superconductor

In an unconventional superconductor, the interplay of scattering off impurities and Andreev processes may lead to different scattering times for electronlike and holelike quasiparticles. Such electron-hole asymmetry appears when the impurity scattering phase shift is intermediate between the Born and unitary limits and leads to an expectation for large thermoelectric effects. Here, we examine the thermoelectric response of a d-wave superconductor connected to normal-metal reservoirs under a temperature bias using a fully self-consistent quasiclassical theory. The thermoelectrically induced quasiparticle current is cancelled by superflow in an open circuit setup, but at the cost of a charge imbalance induced at the contacts and extending across the structure. We investigate the resulting thermopower and thermophase and their dependencies on scattering phase shift, mean free path, and interface transparency. For crystal-axis orientations such that surface-bound zero-energy Andreev states are formed, the thermoelectric effect is reduced as a result of locally reduced electron-hole asymmetry. For a semiballistic superconductor with good contacts, we find thermopowers of order several μV/K, suggesting a thermovoltage measurement as a promising path to investigate thermoelectricity in unconventional superconductors