Query: daniel steininger

title: A VERSATILE UAV NEAR REAL TIME MAPPING SOLUTION FOR DISASTER RESPONSE CONCEPT, IDEAS AND IMPLEMENTATION
abstract: In recent years, the proliferation and further development of unmanned aerial vehicles (UAVs) led to a great number of key technologies, advances and opportunities especially in the realm of time critical applications. UAVs as a platform provide a unique combination of flexibility, affordability and sensor technology which enables the design of cost effective and intriguing services particularly for disaster response. This contribution presents a concept for UAV based near real time mapping system for disaster relief to provide decision making support for first responders particularly for possible disaster scenarios in Austria. We outline our system concept and its respective architecture, discuss requirements from a stakeholder perspective as well as legal regulations and initiatives at an EU level. In the methodology section of this paper, the preliminary data processing pipeline with respect to the near real time orthomosaic generation and the semantic segmentation network are presented. Lastly, first experimental results of the pipeline are shown, and further advances are discussed.

title: RGB D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety
abstract: Automated monitoring and analysis of passenger movement in safety critical parts of transport infrastructures represent a relevant visual surveillance task. Recent breakthroughs in visual representation learning and spatial sensing opened up new possibilities for detecting and tracking humans and objects within a 3D spatial context. This paper proposes a flexible analysis scheme and a thorough evaluation of various processing pipelines to detect and track humans on a ground plane, calibrated automatically via stereo depth and pedestrian detection. We consider multiple combinations within a set of RGBand depth based detection and tracking modalities. We exploit the modular concepts of Meshroom  and demonstrate its use as a generic vision processing pipeline and scalable evaluation framework. Furthermore, we introduce a novel open RGB D railway platform dataset with annotations to support research activities in automated RGB D surveillance. We present quantitative results for multiple object detection and tracking for various algorithmic combinations on our dataset. Results indicate that the combined use of depth based spatial information and learned representations yields substantially enhanced detection and tracking accuracies. As demonstrated, these enhancements are especially pronounced in adverse situations when occlusions and objects not captured by learned representations are present.

title: Human Detection in Crowded Situations by Combining Stereo Depth and Deeply Learned Models
abstract: Human detection in crowded situations represents a challenging task in many practically relevant scenarios. In this paper we propose a passive stereo depth based human detection scheme employing a hierarchically structured tree of learned shape templates for delineating clusters corresponding to humans. In order to enhance the specificity of the depth based detection approach towards humans, we also incorporate a visual object recognition modality in form of a deeply trained model. We propose a simple way to combine the depth and appearance modalities to better cope with complex effects such as heavily occluded and small sized humans, and clutter. Obtained results are analyzed in terms of improvements and shortcomings introduced by the individual detection modalities. Our proposed combination achieves a good accuracy at a decent computational speed in difficult scenarios exhibiting crowded situations. Hence in our view, the presented concepts represent a detection scheme of practical relevance.

title: Temperature dependence of Andreev spectra in a superconducting carbon nanotube quantum dot
abstract: We gratefully acknowledge financial support from the Deutsche Forschungsgemeinschaft within GRK 1570, SFB 689, and the E. Noether program (Hu 1808 1) from Spanish MINECO through Grant No. FIS2011 26516, and from the EU FP7 Project SE2ND

title: Shot Noise Detection in Carbon Nanotube Quantum Dots
abstract: Shot noise investigations in mesoscopic conductors open up a great number of new possibilities for the study of charge carrier statistics as an independent means next to standard dc transport measurements. The present work was aiming at the establishment of a state of the art setup for electrical shot noise detection at low temperatures. Our noise detection system was planned as a twofold amplifier setup based on resonant enhancement of current fluctuations using passive RLC circuits close to the sample stage and distributed two stage amplifier chains including pre amplifiers at cryogenic temperatures. Electrical transport spectroscopy on a carbon nanotube (CNT) based quantum dot device exhibits a peculiar excitation spectrum which we supposed to be of non purely electronic nature. Signatures of electron phonon coupling in the transport were analyzed within the Franck Condon model and confirmed independently by the examination of the Fano factor. Together with numerical model calculations including vibronic modes in a CNT, we were able to identify bosonic excitations as origin of super Poissonian noise enhancements in our device as a complementary method next to standard conductance measurements. Having the Fano factor as an additional tool enables a large diversity of noise experiments in the future.

title: Correlated Motion Based Crowd Analysis in Queueing Situations
abstract: Crowd analysis by automated visual surveillance represents a challenging task in many practically relevant scenarios. In this paper we address the problem of capturing relevant correlated movement within a line formed by waiting pedestrians to estimate the time needed for the last person to reach the queue front. To obtain a waiting time estimate we propose to solve two interlinked problems: queue shape delineation and motion characterization estimating the propagation velocity along the segmented queue. Accordingly, we present a scheme to reliably segment the queue shape by finding and refining an optimum path over time. The optimality condition refers to minimizing its length while maximizing its overlap with observed correlated motion patterns. To capture the collective motion of the crowd within the queue we employ a deformable chain structure to temporally aggregate the relevant short term forward movement by tracking. The resulting tracked chain structure is used to generate a mean forward propagation velocity estimate. The presented approach represents a general analysis scheme, requiring only a set of tracked pedestrians on a calibrated ground plane at every frame. We validate our proposed scheme on two real datasets with time varying queue structures. Based on a comparison to manually set ground truth, obtained results show that queue delineation and waiting time estimates are reliable, can cope with motion clutter and well characterize the waiting behavior and its temporal evolution.

title: Transversal magnetic anisotropy in nanoscale PdNi strips
abstract: We investigate submicron ferromagnetic PdNi thin film strips intended as contact electrodes for carbon nanotube based spintronic devices. The magnetic anisotropy and micromagnetic structure are measured as function of temperature. Contrary to the expectation from shape anisotropy, magnetic hysteresis measurements of Pd0.3Ni0.7 on arrays containing strips of various width point towards a magnetically easy axis in the sample plane, but transversal to the strip direction. Anisotropic magnetoresistance measured on individual Pd0.3Ni0.7 contact strips and magnetic force microscopy images substantiate that conclusion.

title: Transport across a carbon nanotube quantum dot contacted with ferromagnetic leads: Experiment and nonperturbative modeling
abstract: We present measurements of tunneling magnetoresistance (TMR) in single wall carbon nanotubes attached to ferromagnetic contacts in the Coulomb blockade regime. Strong variations of the TMR with gate voltage over a range of four conductance resonances, including a peculiar double dip signature, are observed. The data are compared to calculations in the "dressed second order" (DSO) framework. In this nonperturbative theory, conductance peak positions and linewidths are affected by charge fluctuations incorporating the properties of the carbon nanotube quantum dot and the ferromagnetic leads. The theory is able to qualitatively reproduce the experimental data.

title: Magnetic characterization of PdNi contact electrodes

title: Thermally induced subgap features in the cotunneling spectroscopy of a carbon nanotube
abstract: We report on the nonlinear cotunneling spectroscopy of a carbon nanotube quantum dot coupled to Nb superconducting contacts. Our measurements show rich subgap features in the stability diagram which become more pronounced as the temperature is increased. Applying a transport theory based on the Liouville von Neumann equation for the density matrix, we show that the transport properties can be attributed to processes involving sequential as well as elastic and inelastic cotunneling of quasiparticles thermally excited across the gap. In particular, we predict thermal replicas of the elastic and inelastic cotunneling peaks, in agreement with our experimental results.