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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Marc Eichhorn Fraunhofer IOSB (Institute of Optronics System Technologies and Image Exploitation) Ettlingen Germany Institute of Control Systems (IRS) Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798350345995

So far quantum-mechanical laser theories used approaches based on different but equivalent formulations either relying on a density matrix description or on the Fokker-Planck equation [1], [2]. In all these descriptions an important approximation and assumption have been used since: The outcoupling of photons out of the laser resonator was modeled by a loss term in analogy to what an equivalent intra-cavity absorption of photons would cause to the laser quantum state, i.e., an uncorrelated loss of single photons, thereby incorporating the finite cavity Q-factor into the description of the laser. Although this procedure is consistent in terms of energy and average photon number it lacks the fact that a typical dielectric laser output mirror is not just a uncorrelated photon extracting device like an absorbing or scattering object. As the output coupler is a beam splitter it has a complex action on the incoming intra-cavity photon state. The photon state, therefore, reflected back into the laser resonator is not just shifted to a lower average photon number but is a rather complex combination of various number states that are binomially distributed. The goal of this paper is to investigate the consequences of these findings on the laser photon statistics of continuous-wave lasers, now described by the new master equation including the beam-splitter effect [3]. Therefrom, the detailed balance of probability fluxes (Fig. 1) obtains as and the results with the common laser theory based on absorption-like outcoupling used so far is compared.

关键词： Beam splitters Laser resonators Lasers Mirrors Photon counting Photon statistics

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A Survey on Deep Learning Techniques for Action Anticipation

arXiv

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arXiv 2023年

作者： Zhong, Zeyun Martin, Manuel Voit, Michael Gall, Juergen Beyerer, Jürgen Germany The Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Germany The University of Bonn The Lamarr Institute for Machine Learning and Artificial Intelligence Germany

The ability to anticipate possible future human actions is essential for a wide range of applications, including autonomous driving and human-robot interaction. Consequently, numerous methods have been introduced for action anticipation in recent years, with deep learning-based approaches being particularly popular. In this work, we review the recent advances of action anticipation algorithms with a particular focus on daily-living scenarios. Additionally, we classify these methods according to their primary contributions and summarize them in tabular form, allowing readers to grasp the details at a glance. Furthermore, we delve into the common evaluation metrics and datasets used for action anticipation and provide future directions with systematical discussions. Copyright © 2023, The Authors. All rights reserved.

关键词： Human robot interaction

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6D Pose Estimation on Point Cloud Data through Prior Knowledge Integration: A Case Study in Autonomous Disassembly 31

6D Pose Estimation on Point Cloud Data through Prior Knowled...

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31st CIRP Conference on Life Cycle Engineering, LCE 2024

作者： Wu, Chengzhi Fu, Hao Kaiser, Jan-Philipp Barczak, Erik Tabuchi Pfrommer, Julius Lanza, Gisela Heizmann, Michael Beyerer, Jürgen Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Kaiserstraße 12 Karlsruhe76131 Germany Wbk Institute of Production Science Karlsruhe Institute of Technology Kaiserstraße 12 Karlsruhe76131 Germany Institute of Industrial Information Technology Karlsruhe Institute of Technology Hertzstraße 16 Karlsruhe76187 Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Fraunhoferstraße 1 Karlsruhe76131 Germany

The accurate estimation of 6D pose remains a challenging task within the computer vision domain, even when utilizing 3D point cloud data. Conversely, in the manufacturing domain, instances arise where leveraging prior knowledge can yield advancements in this endeavor. This study focuses on the disassembly of starter motors to augment the engineering of product life cycles. A pivotal objective in this context involves the identification and 6D pose estimation of bolts affixed to the motors, facilitating automated disassembly within the manufacturing workflow. Complicating matters, the presence of occlusions and the limitations of single-view data acquisition, notably when motors are placed in a clamping system, obscure certain portions and render some bolts imperceptible. Consequently, the development of a comprehensive pipeline capable of acquiring complete bolt information is imperative to avoid oversight in bolt detection. In this paper, employing the task of bolt detection within the scope of our project as a pertinent use case, we introduce a meticulously devised pipeline. This multi-stage pipeline effectively captures the 6D information with regard to all bolts on the motor, thereby showcasing the effective utilization of prior knowledge in handling this challenging task. The proposed methodology not only contributes to the field of 6D pose estimation but also underscores the viability of integrating domain-specific insights to tackle complex problems in manufacturing and automation. © 2024 Elsevier B.V.. All rights reserved.

关键词： Pipelines

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Applying Differential Privacy to Medical Questionnaires

Applying Differential Privacy to Medical Questionnaires

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IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom)

作者： Arno Appenzeller Nick Terzer Patrick Philipp Jürgen Beyerer Vision and Fusion Laboratory (IES) Karlsruhe Institute of Technology Karlsruhe Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Karlsruhe Germany

Currently, the medical sector sees a lot of digitization efforts. Besides the already available and growing amount of data there is still a need to receive data from patients. A special form of data donation are medical questionnaires. They come with a fixed set of questions regarding medical conditions and can be performed regularly or once. Such data donations show promising potential for research but come with open questions regarding privacy. There are many examples that show that re-identification is even possible with anonymized data. To mitigate such risks privacy enhancing technologies like Differential Privacy (DP) can be used. This paper presents a procedure for privacy preserving questionnaires using an implementation of DP called RAPPOR. Through its Randomized Response mechanism RAPPOR is well suited to be used with questionnaires. To proof feasibility of this procedure various experiments are conducted that show that this approach can improve privacy while still retaining a good level of utility.

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Event Abstraction in Medical Context Using Self Organizing Maps (CSCI-RTHI)

Event Abstraction in Medical Context Using Self Organizing M...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Patrick Philipp Marie Bommersheim Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Fraunhofer Center for Machine Learning Karlsruhe Germany

With the digital transformation in medicine, enormous amounts of data are being generated and are available for analysis. Process mining techniques can be utilized to extract process models from this data. On the one side these process models typically provide detailed, fine-granular activitiy descriptions. But on the other hand these models become increasingly less recognizable. Therefore, in this contribution we explore the use of Self Organizing Maps for an event abstraction in the medical context. Our approach achieved promising results on a publicly available sepsis data set.

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Joint Parameter and State-Space Modelling of Manufacturing Processes using Gaussian Processes

Joint Parameter and State-Space Modelling of Manufacturing P...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Saksham Kiroriwal Julius Pfrommer Hendrik Mende Robert H. Schmitt Jurgen Beyerer Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Germany Fraunhofer Institute of Production Technology IPT Germany WZL: Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University Karlsruhe Institute of Technology Germany

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Manufacturing process optimization is an open question, where Bayesian decision theoretic methods have shown considerable promise. One such is Bayesian optimization, with Gaussian Process (GP) surrogate model. This paper explores Gaussian Processes networks to jointly use parameter and observed state to predict the output(s) of a manufacturing process. The Gaussian process network that represents the paths from parameters to state-space to tasks, provides a methodology to ‘look inside’ the black-box of complex manufacturing processes. We present a comparative analysis of this method against the multi-task Gaussian processes and single-task counterparts, highlighting the benefits and drawbacks of each in modelling the behavior of such processes. We show the benefits of the proposed approach using numerical experiments. We show that we are able to improve the output prediction by additional sensor observations from inside the process at training time without needing those sensor observations for predicting product quality given the process parameters.

关键词： Training Manufacturing processes Gaussian processes Multitasking Product design Numerical models Bayes methods Quality assessment Informatics Optimization

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imager performance assessment with TRM4 version 3: An overview 18

Imager performance assessment with TRM4 version 3: An overvi...

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Electro-Optical and Infrared systems: Technology and Applications XVIII and Electro-Optical Remote Sensing XV 2021

作者： Pérez, José Steiner, Dov Keßler, Stefan Fraunhofer IOSB Ettlingen Fraunhofer Institute of Optronics System Technologies and Image Exploitation Germany IARD - Sensing Solutions Ltd. Kibbutz Yagur30065 Israel

ISBN: (数字)9781510645776

ISBN: (纸本)9781510645769

Model-based performance assessment is a valuable approach in the process of designing or comparing electrooptical and infrared imagers since it alleviates the need for expensive field measurement campaigns. TRM4 serves this purpose and is primarily used to calculate the range performance based on parameters of the imaging system and the environmental conditions. It features a validated approach to consider aliasing in the performance assessment of sampled imagers. This paper highlights new features and major changes in TRM4.v3, which is to be released in autumn 2021. TRM4.v3 includes the calculation of an image quality metric based on the National imagery Interpretability Rating Scale (NIIRS). The NIIRS value computation is based on the latest version of the General image Quality Equation. This extends the performance assessment capability of TRM4 in particular to imagers used for aerial imaging. The three-dimensional target modelling was revised to cope with a wider range of scenarios: from ground imaging of aerial targets against a sky background to aerial imaging of ground targets, including groundto-ground imaging. For imagers working in the visible to the SWIR spectral range, TRM4.v3 provides not only an improved comparison basis between lab measurements and modelling, but also allows direct integration of measured device data. This is achieved by introducing and computing (in analogy to the Minimum Temperature Difference Perceived used for thermal imagers) the so-called Minimum Contrast Perceived (MCP). This device figure of merit is similar to the Minimum Resolvable Contrast (MRC) but also applicable at frequencies above Nyquist frequency. Using measured MCP or MRC data, range performance can be calculated for devices such as cameras, telescopic sights and night vision goggles. In addition, the intensified camera module introduced in a previous publication was further elaborated and a comparison to laboratory measurement results is presented. Lastly, the grap

关键词： image quality

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A retracing free-space optical connection for reliable underwater optical communications 7

A retracing free-space optical connection for reliable under...

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Environmental Effects on Light Propagation and Adaptive systems VII 2024

作者： Paglierani, P. Di Giancamillo, M. Martinelli, M. Gladysz, S. Stipanov, M. Zappa, G. Panipinto, M. Alves, J. NATO STO Centre for Maritime Research and Experimentation Viale S. Bartolomeo 400 La Spezia19126 Italy Politecnico di Milano Department of Electronics Information and Bioengineering Milano20133 Italy Fraunhofer IOSB Ettlingen Fraunhofer Institute of Optronics System Technologies and Image Exploitation Gutleuthausstr. 1 Ettlingen76275 Germany Holcombe Department of Computer and Electrical Engineering Clemson University ClemsonSC29634 United States

ISBN: (纸本)9781510680968

To establish a free-space underwater optical connection between a transmitter and a receiver suitable for operation in the single photon regime, techniques must be developed to compensate for: a) rotational and translational motions of both the transmitter and the receiver, b) their vibrations, and c) turbulence-induced deformations of the wavefront leading to beam wander, scintillation and beam spreading. The purpose of this work is to present and discuss experimental results obtained using a pseudo phase-conjugated mirror placed at the end of an underwater optical path disturbed by artificially induced turbulence. This configuration emulates a scenario whereby a modulated retroreflector is used to transmit the data back to the laser transmitter. The measurements obtained with the proposed retracing optical connection are found to be promising and pave the way for the use of this technique for quantum communications. © 2024 SPIE.

关键词： Quantum communication

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SynMotor: A Benchmark Suite for Object Attribute Regression and Multi-task Learning

arXiv

引用

arXiv 2023年

作者： Wu, Chengzhi Qiu, Linxi Zhou, Kanran Pfrommer, Julius Beyerer, Jürgen Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Fraunhofer Center for Machine Learning Karlsruhe Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Karlsruhe Germany

In this paper, we develop a novel benchmark suite including both a 2D synthetic image dataset and a 3D synthetic point cloud dataset. Our work is a sub-task in the framework of a remanufacturing project, in which small electric motors are used as fundamental objects. Apart from the given detection, classification, and segmentation annotations, the key objects also have multiple learnable attributes with ground truth provided. This benchmark can be used for computer vision tasks including 2D/3D detection, classification, segmentation, and multi-attribute learning. It is worth mentioning that most attributes of the motors are quantified as continuously variable rather than binary, which makes our benchmark well-suited for the less explored regression tasks. In addition, appropriate evaluation metrics are adopted or developed for each task and promising baseline results are provided. We hope this benchmark can stimulate more research efforts on the sub-domain of object attribute learning and multi-task learning in the future. Copyright © 2023, The Authors. All rights reserved.

关键词： Computer vision

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On the classifier performance for simulation based debris detection in sar imagery 24

On the classifier performance for simulation based debris de...

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2021 24th ISPRS Congress Commission I: Imaging Today, Foreseeing Tomorrow

作者： Kuny, S. Hammer, H. Schulz, K. Fraunhofer IOSB Institute of Optronics System Technologies and Image Exploitation Ettlingen Germany Institute of Photogrammetry and Remote Sensing IPF Karlsruhe Institute of Technology KIT Germany

Urban areas struck by disasters such as earthquakes are in need of a fast damage detection assessment. A post-event SAR image often is the first available image, most likely with no matching pre-event image to perform change detection. In previous work we have introduced a debris detection algorithm for this scenario that is trained exclusively with synthetically generated training data. A classification step is employed to separate debris from similar textures such as vegetation. In order to verify the use of a random forest classifier for this context, we conduct a performance comparison with two alternative popular classifiers, a support vector machine and a convolutional neural network. With the direct comparison revealing the random forest classifier to be best suited, the effective performance on the prospect of debris detection is investigated for the post-earthquake Christchurch scene. Results show a good separation of debris from vegetation and gravel, thus reducing the false alarm rate in the damage detection operation considerably. © Copyright: Author(s) 2021.

关键词： Damage detection

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