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International Optical Design Conference, IODC 2021

作者： Li, Zheng Taphanel, Miro Langle, Thomas Beyerer, Jurgen Fraunhofer Institute of Optronics System Technologies and Image Exploitation Fraunhoferstr. 1 Karlsruhe76131 Germany Vision and Fusion Lab Karlsruhe Institute of Technology c/o Technologiefabrik Karlsruhe76131 Germany

ISBN: (纸本)9781943580880

In traditional confocal microscopes, high resolution and large fields of view are difficult to achieve simultaneously by microscope objectives, which limit the space-bandwidth products of the systems. With the proposed diffractive lens arrays, an objective with a low numerical aperture can have much higher resolution while maintaining its large field of view. Application of the diffractive lens arrays in uorescence microscopy is presented in this work. The resolution enhancement is demonstrated by experiments with the uorescent beads. © 2021 OSA - The Optical Society. All rights reserved.

关键词： Bandwidth

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GridSort: image-based Optical Bulk Material Sorting Using Convolutional LSTMs

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IFAC-PapersOnLine 2023年第2期56卷 4620-4626页

作者： Marcel Reith-Braun Albert Bauer Maximilian Staab Florian Pfaff Georg Maier Robin Gruna Thomas Längle Jürgen Beyerer Harald Kruggel-Emden Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory Karlsruhe Institute of Technology 76131 Karlsruhe Germany Chair of Mechanical Process Engineering and Solids Processing Technische Universität Berlin 10587 Berlin Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation 76131 Karlsruhe Germany

Optical sorters separate particles of different classes by first detecting them while they are transported, e.g., on a conveyor belt, and subsequently bursting out particles of undesired classes using compressed air nozzles. Currently, the most promising results are achieved by predictive tracking, a multitarget tracking approach based on extracted midpoints from area-scan camera images that analyzes the particles’ motion and activates the nozzles accordingly. However, predictive tracking requires expert knowledge for setup and preceding object detection. Moreover, particle shapes are only considered implicitly, and the need to solve an association problem rises the computational complexity of the algorithm. In this paper, we present GridSort, an image-based approach that forecasts the scene at the nozzle array using a convolutional long short-term memory neural network and subsequently extracts nozzle activations, thus circumventing the aforementioned weaknesses. We show how GridSort can be trained in an unsupervised fashion and evaluate it using a coupled discrete element–computational fluid dynamics simulation of an optical sorter. We compare our method with predictive tracking in terms of sorting accuracy and demonstrate that it is an easy-to-apply alternative while achieving state-of-the-art results.

关键词： Monitoring of product quality and control performance Neural networks in process control Machine learning methods and applications Artificial intelligence in mining, minerals and metals Process monitoring and fault diagnosis

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Supporting the Incorporation of Individual Patient Preferences for Decision Support in Breast Cancer Therapy

Supporting the Incorporation of Individual Patient Preferenc...

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International Conference on Computational Science and Computational Intelligence (CSCI)

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

ISBN: (纸本)9781665458429

With the rise of personalized medicine, the number of individualized treatment options and related decisions is increasing tremendously. Thereby, the acquisition, incorporation and representation of the patient’s individual preferences in upcoming, modern, AI-based medical decision support systems play a decisive role. E.g., for patients with advanced breast cancer, there are various therapeutic options associated with different outcomes to choose from. In our contribution we show a first approach to model Preference Elicitation (PE) via card sorting using a utility function. Based on this, we present further ideas for extending and improving the approach.

关键词： Decision support systems Scientific computing Precision medicine Computational modeling Breast cancer Computational intelligence Sorting

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Spatial Augmented Reality in Industrial Environments - An Approach for Improved Hand-Tracking Using Combined Computer Vision technologies

Spatial Augmented Reality in Industrial Environments - An Ap...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Christoph Wächter Sahar Deppe Carsten Röcker Eckelmann FCS AG Herford Germany Fraunhofer Institute of Optronics System Technologies and Image Exploiation Lemgo Germany TH OWL University of Applied Sciences and Arts Lemgo Germany

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374506

Spatial augmented reality is playing an increasingly important role in the design of digital assistance systems for industrial applications. Most of these systems use integrated computer vision technologies for supporting direct interactions in the physical workspace of the user. While these systems work well under lab conditions, field tests in real production environments revealed shortcomings of the underlying computer vision approaches with regard to their reliability. In this paper, we present a concept combing machine learning with the theories of Dempster-Schafer and fuzzy set for improved classification and reliability. For the classification, the Mediapipe-Hand machine learning framework and a segmentation-based method were combined. The fusion with the indices and the classification results is done with fuzzy inference. The subsequent results are merged with Dempster's combination rule. The results proved that the presented concept increases the reliability of the detection up to 97.8 percent.

关键词： Computer vision Visualization Fuzzy sets Three-dimensional displays Spatial augmented reality Machine learning Virtual reality

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Exploring data analysis methods to find correlations between physiological data and flow 15

Exploring data analysis methods to find correlations between...

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15th International Conference on Interfaces and Human Computer Interaction, IHCI 2021 and 14th International Conference on Game and Entertainment technologies, GET 2021 - Held at the 15th Multi-Conference on Computer Science and Information systems, MCCSIS 2021

作者： Kannegieser, Ehm Hensler, Anita Fraunhofer Institute of Optronics System Technologies and Image Exploitation Fraunhoferstraße. 1 Karlsruhe76131 Germany Hochschule Karlsruhe – University of Applied Sciences Moltkestraße 30 Karlsruhe76133 Germany

ISBN: (纸本)9789898704313

In learning situations, achieving Flow, the state of ideal experience of an activity, can greatly support the learning efficacy. Utilizing this connection by detecting and measuring Flow during the learning activity could potentially help to improve the learning rate in Serious Games. In a prior study aimed towards developing a tool to link Flow to physiological measurements, no meaningful correlations were found. However, this does not rule out the existence of such a correlation and different analysis methods might deliver results that are more favorable. In this work in progress paper, the previously collected data is revisited and an approach is outlined to explore the use of a multitude of machine learning methods, based on multiple physiological measurements, to detect Flow and to investigate, whether it provides adequate tools to gain further insight into the link between physiological data and Flow states. © MCCSIS *** right reserved.

关键词： Serious games

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Information acquisition on pedestrian movements in urban traffic with a mobile multi-sensor system 24

Information acquisition on pedestrian movements in urban tra...

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

作者： Borgmann, Bjorn Hebel, Marcus Arens, Michael Stilla, Uwe Fraunhofer IOSB Fraunhofer Institute of Optronics System Technologies and Image Exploitation Fraunhofer Center for Machine Learning Gutleuthausstr. 1 Ettlingen76275 Germany Photogrammetry and Remote Sensing Technische Universitaet Muenchen Arcisstr. 21 Munich80333 Germany

This paper presents an approach which combines LiDAR sensors and cameras of a mobile multi-sensor system to obtain information about pedestrians in the vicinity of the sensor platform. Such information can be used, for example, in the context of driver assistance systems. In the first step, our approach starts by using LiDAR sensor data to detect and track pedestrians, benefiting from LiDAR's capability to directly provide accurate 3D data. After LiDAR-based detection, the approach leverages the typically higher data density provided by 2D cameras to determine the body pose of the detected pedestrians. The approach combines several state-of-the-art machine learning techniques: it uses a neural network and a subsequent voting process to detect pedestrians in LiDAR sensor data. Based on the known geometric constellation of the different sensors and the knowledge of the intrinsic parameters of the cameras, image sections are generated with the respective regions of interest showing only the detected pedestrians. These image sections are then processed with a method for image-based human pose estimation to determine keypoints for different body parts. These keypoints are finally projected from 2D image coordinates to 3D world coordinates using the assignment of the original LiDAR points to a particular pedestrian. © 2021 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. All rights reserved.

关键词： Cameras

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Testing automated operation and control algorithms for distribution grids using a co-simulation environment

Testing automated operation and control algorithms for distr...

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ETG-Kongress 2021: Von Komponenten bis zum Gesamtsystem fur die Energiewende - ETG Congress 2021: From Components to the Overall system for the Energy Turnaround

作者： Schoen, Andrea Ringelstein, Jan Hammermeister, Irene Braun, Martin Wille-Haussmann, Bernhard Marchand, Sophie Ruhe, Stephan Nicolai, Steffen Fraunhofer Institute for Energy Economics and Energy System Technology Kassel Germany University of Kassel Department of Energy Management and Power System Operation Kassel Germany Fraunhofer Institute for Solar Energy Systems Freiburg Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation Advanced System Technology Branch Ilmenau Germany Fraunhofer Cluster of Excellence Integrated Energy Systems Germany

ISBN: (纸本)9783800755493

This publication presents a co-simulation framework that enables joint simulation experiments by multiple remote laboratories for analyses of smart grid energy systems that can also include power hardware-in-the-loop. It introduces a proof of concept where individual parts of an example electrical grid are modelled at three geographically distributed fraunhofer institutes. The models differ greatly in terms of their used tools, functionality, control algorithms, and time resolution. Real-time and non-real-time systems can be combined as well. The framework is developed within the Distributed Grid Lab of the fraunhofer Cluster of Excellence Integrated Energy systems (CINES) [1]. The goal is to allow laboratory collaboration for addressing the needs of users such as manufacturers, grid operators and research institutions to test their grid automation solutions before field deployment. This testing can be done considering the interactions of various components and solutions at different remotely located testing facilities without needing to use the same hardware and software setup. A demonstrator is developed to highlight these capabilities. © VDE VERLAG GMBH. Berlin. Offenbach

关键词： Real time systems

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Mapping Shallow Water Environments using a Semi-Autonomous Multi-Sensor Surface Vehicle

Mapping Shallow Water Environments using a Semi-Autonomous M...

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2020 Global Oceans: Singapore - U.S. Gulf Coast, OCEANS 2020

作者： Kleiser, Dominik Albrecht, Alexander Emter, Thomas Zube, Angelika Petereit, Janko Woock, Philipp Fraunhofer Center for Machine Learning Fraunhofer IOSB Karlsruhe Fraunhofer Institute of Optronics System Technologies and Image Exploitation Karlsruhe Germany

ISBN: (纸本)9781728154466

We show a multi-sensor platform for mapping tasks of shallow water areas like rivers or harbors, both under and above the waterline simultaneously. The autonomy of the platform is realized just by integrating the sensors and the autonomy box which provides, i.a., the motion planning. The sensor data is synchronized purely in software by a newly developed timestamping filter. Maps obtained by the autonomously driven platform are shown as an example for the platform capabilities. © 2020 IEEE.

关键词： Mapping

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RangeBird: Multi View Panoptic Segmentation of 3D Point Clouds with Neighborhood Attention

RangeBird: Multi View Panoptic Segmentation of 3D Point Clou...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Fabian Duerr Hendrik Weigel Jü rgen Beyerer Audi AG Ingolstadt Germany Vision and Fusion Lab Karlsruhe Institute of Technology Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation Fraunhofer Center for Machine Learning Karlsruhe Germany

Panoptic segmentation of point clouds is one of the key challenges of 3D scene understanding, requiring the simultaneous prediction of semantics and object instances. Tasks like autonomous driving strongly depend on these information to get a holistic understanding of their 3D environment. This work presents a novel proposal free framework for lidar-based panoptic segmentation, which exploits three different point cloud representations, leveraging their strengths and compensating their weaknesses. The efficient projection-based range view and bird's eye view are combined and further extended by a point-based network with a novel attention-based neighborhood aggregation for improved semantic features. Cluster-based object recognition in bird's eye view enables an efficient and high-quality instance segmentation. Semantic and instance segmentation are fused and further refined by a novel instance classification for the final panoptic segmentation. The results on two challenging large-scale datasets, nuScenes and SemanticKITTI, show the success of the proposed framework, which outperforms all existing approaches on nuScenes and achieves state-of-the-art results on SemanticKITTI.

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Towards a One-Stop-Shop Solution for the Application of Data-Driven Value-Adding Services in Production

Towards a One-Stop-Shop Solution for the Application of Data...

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International Conference on Emerging technologies and Factory Automation (ETFA)

作者： Magnus Redeker Dennis Quirin Rafael Schroeder Tobias Klausmann Alexander Löwen Alexander Wollbrink Heiko Stichweh Simon Althoff Amelie Bender Walter Sextro Marc Hesse Fraunhofer IOSB IOSB-INA Lemgo Fraunhofer Institute of Optronics System Technologies and Image Exploitation Bielefeld University Cognitronics & Sensor Systems Friedrich Remmert GmbH R & D Systems Engineering - Lenze SE Faculty of Mechanical Engineering Chair of Dynamics and Mechatronics Paderborn University Paderborn Germany Weidmüller Group

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

The holistic application of data-driven value-adding services (DDSs) to shop-floor assets (SFAs; e.g. equipment, machines, components) is a major obstacle, particularly for small and medium-sized enterprises (SMEs): Due to the high complexity and required expertise in various disciplines. It is necessary to i) select suitable DDSs for a relevant component in production, ii) provide data for their training, iii) deploy the DDSs in the given IT/OT infrastructure, and iv) setup data-streams between SFAs, DDSs, and dashboards. Currently, many companies are implementing flagship projects that go through the necessary steps for individual components, but these isolated solutions are not scalable due to the need for manual intervention. This paper describes how to completely automatize the four steps and their consolidation in a scalable Industry 4.0 one-stop-shop solution. To achieve this goal, each asset is equipped with an Asset Administration Shell (AAS) that specifies, in particular, the represented asset's capabilities, the data required to apply such a capability and the data generated by a capability. Based on the AASs of SFAs, DDSs, and computing resources (CRs), a matching service suggests automatically which DDSs would add value to which SFAs and, for each SFA-DDS match, in which CR to deploy the DDS. A trade fair demonstration provides strong support for the statements made: The one-stop-shop solution including the automatic matching greatly simplifies the application of data-driven services and, in some cases, even makes it possible at all.

关键词： Training Space vehicles Production systems Remotely guided vehicles Semantics Sensors Laser beam cutting Streams Space stations Monitoring

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