Aktuelle Publikationen

Oktober 2020

Hybrid data and model driven algorithms for angular power spectrum estimation

Renato L. G. Cavalcante, Slawomir Stanczak

We propose two algorithms that use both models and datasets to estimate angular power spectra from channel covariance matrices in massive MIMO systems. The first algorithm is an iterative fixed-point method that solves a hierarchical problem. It uses model knowledge to narrow down candidate angular power spectra to a set that is consistent with a measured covariance matrix. Then, from this set, the algorithm selects the angular power spectrum with minimum distance to its expected value with respect to a Hilbertian metric learned from data. The second algorithm solves an alternative optimization problem with a single application of a solver for nonnegative least squares programs. By fusing information obtained from datasets and models, both algorithms can outperform existing approaches based on models, and they are also robust against environmental changes and small datasets.


Oktober 2020

Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements

Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand

Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV- 2 pandemic. In this work we propose an approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies.


September 2020

637 μW emitted terahertz power from photoconductive antennas

Robert Kohlhaas, Steffen Breuer, Lars Liebermeister, Simon Nellen, Milan Deumer, Mykhaylo P. Semtsiv, William Ted Masselink, Björn Globisch

We present photoconductive terahertz (THz) emitters based on rhodium (Rh) doped InGaAs for time-domain spectroscopy (TDS). The emitters feature a record high THz power of 637 µW. In combination with InGaAs:Rh receivers, a 6.5 THz bandwidth and a record peak dynamic range of 111 dB can be achieved. These improvements enable layer thickness measurement systems with unprecedented resolution and accuracy.


August 2020

Effect of Optical Feedback on the Wavelength Tuning in DBR Lasers

Magnus Happach, David de Felipe Mesquida, Victor Nicolai Friedhoff, Gelani Irmscher, Martin Kresse, Moritz Kleinert, Crispin Zawadzki, Walter Brinker, Martin Möhrle, Norbert Keil, Werner Hofmann, Martin Schell

Optical feedback has an impact on the tunability of lasers. We created a model of a tunable distributed Bragg reflector (DBR) laser describing the effect of optical feedback from a constant reflector distance on the wavelength tuning. Theoretical and experimental results are in good agreement. A further discussion of the model sheds light on design rules to reduce the effect of optical feedback on the tuning behavior. We introduced a new parameter called mode loss difference (MLD) as a metric for the feedback tolerance of the tuning behavior. A large MLD indicates higher tolerance of the laser to cavity length variations.


August 2020

Accurate and Robust Neural Networks for Face Morphing Attack Detection

Clemens Peter Seibold, Peter Eisert, Anna Hilsmann, Wojciech Samek

A morphed face image is a fusion of two face images and represents biometrics of two different subjects. Embedded in an official document, it can cause immense damage, since both subjects can claim its ownership and thus share an identity. In this paper, we propose and compare different neural network training schemes based on alternations of training data to obtain accurate and robust detectors for such kind of fraud. In addition, we use layer-wise relevance propagation (LRP) to analyze the differently trained networks in depth.


August 2020

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints

Felix Sattler, Klaus-Robert Müller, Wojciech Samek

Federated Learning (FL) is currently the most widely adopted framework for collaborative training of (deep) machine learning models under privacy constraints. However, FL yields suboptimal results if the local clients’ data distributions diverge. The proposed Clustered FL approach tackles the problem by identifying diverging clients and grouping them into separate clusters.


Juli 2020

Monolithically Integrated InP-Based Polarization Rotator-Splitter with Simplified Fabrication Process

Hendrik Boerma, Patrick Runge, Martin Schell, Felix Ganzer, Shahram Keyvaninia

Polarization division multiplexing doubles the transmission capacity of optical communication systems. For such systems, splitters separating the TE from the TM mode are indispensable components. We design and manufacture an integrated InP-based polarization rotator-splitter. The device is simplified in manufacturing and has a polarization extinction ratio of 17 dB over 60 nm optical bandwidth.


April 2020

Going beyond Free Viewpoint: Creating Animatable Volumetric Video of Human Performances

Anna Hilsmann, Oliver Schreer, Peter Eisert, Ingo Feldmann, Philipp Fechteler, Wolfgang Paier, Wieland Morgenstern

We present an end-to-end pipeline for the creation of high-quality animatable volumetric video content of human performances. Going beyond the application of free-viewpoint volumetric video, we allow re-animation of an actor’s performance through (i) the enrichment of the captured data with semantics and animation properties and (ii) hybrid geometry- and video-based animation combined with neural infilling.


März 2020

High performance BH InAs/InP QD and InGaAsP/InP QW mode-locked lasers as comb and pulse sources

Marlene Zander, Martin Schell, Martin Moehrle, Wolfgang Rehbein, Jan C. Balzer, Steffen Breuer, Dieter Franke, Kevin Kolpatzeck

Coherent comb lasers may serve as a source for multiwavelength modulators in short reach transmission, or for phase controlled OFDM channels in long reach. We explore and compare quantum dot (QD) and quantum well (QW) lasers with more than 33 channels in the DWDM 50 GHz grid, thus enabling > 1 Tb/s optical transmission. In addition, the mode-locked devices can be applied as pulse sources with < 500 fs pulses by using a simple SMF.


Februar 2020

Hybrid Human Modeling: Making Volumetric Video Animatable

Peter Eisert, Anna Hilsmann

Photo-realistic modeling and rendering of humans is extremely important for VR environments. While purely computer graphics modeling can achieve highly realistic human models, achieving real photo-realism with these models is computationally extremely expensive. Therefore, we enrich volumetric video with semantics and animation properties to make photo-realistic volumetric video animatable.


Februar 2020

Determination of the optical properties of cholesteatoma in the spectral range of 250 to 800 nm

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Florian Uecker, Philipp Arens, Steffen Dommerich

We determine the absorption and scattering coefficients of cholesteatoma and bone. In the near-UV and visual spectrum, clear differences exist between both tissues. These differences reveal the future possibility to detect and identify, automatically or semi-automatically, cholesteatoma tissue for active treatment decisions during image-guided surgery leading to a better surgical outcome.


Januar 2020

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks

Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marban, Talmaj Marinc, David Neumann, Tung Nguyen, Ahmed Osman, Heiko Schwarz, Detlev Marpe, Thomas Wiegand, Wojciech Samek

This paper presents DeepCABAC, a universal compression algorithm for deep neural networks (DNNs) that through its adaptive, context-based rate modeling, allows an optimal quantization and coding of parameters. It compresses DNNs up to 5% of their original size with no accuracy loss and has been selected as basic compression technology for the emerging MPEG-7 part 17 standard on DNN compression.


August 2019

Projection Distortion-based Object Tracking in Shader Lamp Scenarios

Niklas Gard, Peter Eisert, Anna Hilsmann

We enable dynamic projection mapping on 3d objects and present a model-based tracking strategy for projector camera-systems, which directly takes advantage from the projected content for pose estimation. Our method establishes a distortion free projection by first analysing and then correcting the distortion of the projection in a closed loop. Therefor an optical flow-based model is extended to the geometry of a projector-camera unit. We evaluate our procedure with real and synthetic images and obtain very precise registration results.


Juli 2019

Determination of Optical Properties of Human Tissues obtained from Parotidectomy in the Spectral Range of 250 to 800 nm

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Florian Uecker, Steffen Dommerich

We analyze five healthy soft tissue types as well as tumor tissue in terms of absorption and scatter coefficients in the spectral range of 250 to 800 nm. The spectral properties of the analyzed tissue types show relevant differences in this specific spectral range. This knowledge can be used for different medical and biomedical application areas as computer-aided diagnostics, intraoperative image guidance and histological analysis.


März 2019

Interactive and Multimodal-based Augmented Reality for Remote Assistance using a Digital Surgical Microscope

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Jean-Claude Rosenthal, Florian Uecker, Armin Schneider, Falko Schmid, Michael Bauer

This paper introduces the current running project MultiARC, which has the aim to combine stereoscopic measurements and scene reconstruction with hyperspectral tissue differentiation in a surgical microscope and 3D endoscope for image-guided surgery.


Oktober 2018

Animatable 3D Model Generation from 2D Monocular Visual Data

Philipp Fechteler, Peter Eisert, Anna Hilsmann, Lisa Kausch

In this paper, we present an approach for creating animatable 3D models from temporal monocular image acquisitions of non-rigid objects. During deformation, the object of interest is captured with only a single camera under full perspective projection. The aim of the presented framework is to obtain a shape deformation model in terms of joints and skinning weights that can finally be used for animating the model vertices.


Oktober 2018

Markerless Closed-Loop Projection Plane Tracking for Mobile Projector-Camera Systems

Niklas Gard, Peter Eisert

The recent trend towards miniaturization of mobile projectors is allowing new forms of information presentation and interaction. Projectors can easily be moved freely in space either by humans or by mobile robots. This paper presents a technique to dynamically track the orientation and position of the projection plane only by analyzing the distortion of the projection by itself, independent of the presented content. It allows distortion-free projection with a fixed metric size for moving projector-camera systems.


März 2018

Automatic Analysis of Sewer Pipes Based on Unrolled Monocular Fisheye Images

Johannes Wolf Künzel, Peter Eisert, Thomas Werner, Ronja Möller, Jan Waschnewski, Ralf Hilpert

The task of detecting and classifying damages in sewer pipes offers an important application area for computer vision algorithms. This paper describes a system, which is capable of accomplishing this task solely based on low quality and severely compressed fisheye images from a pipe inspection robot. Relying on robust image features, we estimate camera poses, model the image lighting, and exploit this information to generate high quality cylindrical unwraps of the pipes' surfaces. Based on the generated images, we apply semantic labeling based on deep convolutional neural networks to detect and classify defects as well as structural elements.



Ergebnisse pro Seite10ǀ20ǀ30