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University of Rostock, Germany

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24 Papers

Lightweight Coordination of Multiple Independent Visual Analytics Tools

Topics: Visual Data Analysis and Knowledge Discovery; Visualization Taxonomies and Models

Authors: Hans-Jörg Schulz ¹ , Martin Röhlig ² , Lars Nonnemann ³ , Mario Aehnelt ³ , Holger Diener ³ , Bodo Urban ³ and Heidrun Schumann ²

Affiliations: ¹ Department of Computer Science, Aarhus University, Åbogade 34, 8200 Aarhus N and Denmark , ² Institute of Computer Science, University of Rostock, Albert-Einstein-Straße 22, 18059 Rostock and Germany , ³ Fraunhofer Institute of Computer Graphics Research, Joachim-Jungius-Straße 11, 18059 Rostock and Germany

Digital Object Identifier: 10.5220/0007571101060117

Proceedings of IVAPP 2019, ISBN: 978-989-758-354-4

Quick Abstract

With the advancement of Visual Analytics (VA) and its spread into various application fields comes along a specialization of methods and tools. This adds complexity and requires extra effort when devising domain-dependent VA solutions, as for every new domain question a new specialized tool or framework must be developed. In this paper, we investigate the possibility of using and re-using existing tools – domain-dependent and general-purpose – by loosely coupling them into specialized VA tool ensembles as needed. We call such coupling among independent tools lightweight coordination, as it is minimally-invasive, pair-wise, and opportunistic in utilizing whichever interface a VA tool offers. We propose the use of lightweight coordination for managing the workflow, the data flow, and the control flow among VA tools, and we show how it can be supported with suitable setups of the multiple tool UIs involved. This concept of lightweight coordination is exemplified with a health care scenario, where an ensemble of independent VA tools is used in a concerted way to pursue the visual analysis of a patient’s troublesome vital data.

Related Ontology Subjects/Areas/Topics (5)

Abstract Data Visualization		General Data Visualization		Visualization Taxonomies and Models
Computer Vision, Visualization and Computer Graphics		Visual Data Analysis and Knowledge Discovery

Applying the PROSA Reference Architecture to Enable the Interaction between the Worker and the Industrial Robot - Case Study: One Worker Interaction with a Dual-Arm Industrial Robot

Topics: Multi-Agent Systems; Distributed Problem Solving; Agent Models and Architectures; Task Planning and Execution; Agent Platforms and Interoperability

Authors: Ahmed R. Sadik and Bodo Urban

Affiliation: University of Rostock and Fraunhofer Institute for Computer Graphic Research IGD, Germany

Digital Object Identifier: 10.5220/0006191801900199

Proceedings of ICAART 2017, ISBN: 978-989-758-219-6

Quick Abstract

Involving an industrial robot in a close physical interaction with the worker became quite possible, as a result of the availability of different collaborative industrial robots in the market. The physical cooperation between the industrial robot and the worker usually done under the umbrella of the flexible manufacturing paradigm, where both the industrial robot and the worker need to change their tasks fast and efficiently, to cope with the changes in the manufacturing process. This means that a reliable manufacturing control system must stand behind this physical interaction to achieve the proper communication interaction. A holonic control architecture is an ideal solution for this problem. Therefore, during this research we study the most commonly applied model of the holonic control architecture, then we apply this architecture on our case study, where one worker cooperates with a dual-arm industrial robot to build and produce any new product. Also the research uses the worker’s hand gesture recognition as a method to interact with the industrial robot during the execution of a cooperative production scenario.

Related Ontology Subjects/Areas/Topics (14)

Agent Models and Architectures	Distributed and Mobile Software Systems	Multi-Agent Systems
Agent Platforms and Interoperability	Distributed Problem Solving	Software Engineering
Agents	Enterprise Information Systems	Symbolic Systems
Artificial Intelligence	Knowledge Engineering and Ontology Development	Task Planning and Execution
Artificial Intelligence and Decision Support Systems	Knowledge-Based Systems

Towards a Complex Interaction Scenario in Worker-cobot Reconfigurable Collaborative Manufacturing via Reactive Agent Ontology - Case-study: Two Workers in Cooperation with One Cobot

Topics: Decision Support Systems; Knowledge Representation; Human-Machine Cooperation; Applications and Case-Studies; Enterprise Engineering

Authors: Ahmed R. Sadik and Bodo Urban

Affiliation: University of Rostock and Fraunhofer Institute for Computer Graphic Research IGD, Germany

Digital Object Identifier: 10.5220/0006487200270038

Proceedings of KEOD 2017, ISBN: 978-989-758-272-1

Quick Abstract

Close Human-Robot Interaction (HRI) has been a great focus of research for the last decades. The outcomes of this focus is a new field in industrial robotics called collaborative robotics. A collaborative robot (cobot) is usually an industrial robot designed to operate safely in a shared work environment with the human worker. This in contrast to conventional Industrial Robots (IRs) which are operating in isolation from the worker workspace, the cobot is changing the concept of automation from fully automated operations to semi-autonomous operations, where the decisions of the worker will influence the actions of the cobot and vice-versa. Therefore, a communication and information control framework must exist to connect the worker and the cobot together to fulfil this semi-autonomous paradigm. This framework should be able to provide a method to represent the common knowledge which can support the collaborative manufacturing between the worker and the cobot. During this research we are proposing an ontology-based Holonic Control Architecture (HCA) as a proper solution to share and communicate the knowledge needed to achieve complex interaction scenarios between the worker and the cobot.

Related Ontology Subjects/Areas/Topics (17)

Applications and Case-studies	Decision Support Systems	Human-Machine Cooperation
Artificial Intelligence	Decision Support Systems, Remote Data Analysis	Knowledge Engineering and Ontology Development
Business Analytics	e-Business	Knowledge Representation
Cardiovascular Technologies	Enterprise Engineering	Knowledge-Based Systems
Computing and Telecommunications in Cardiology	Enterprise Information Systems	Symbolic Systems
Data Engineering	Health Engineering and Technology Applications

Visual Interactive Creation of Geo-located Networks

Topics: Graph Visualization; Uncertainty Visualization

Authors: Felix Brodkorb ¹ , Manuel Kopp ¹ , Arjan Kuijper ² and Tatiana von Landesberger ¹

Affiliations: ¹ TU Darmstadt, Germany , ² Fraunhofer IGD, Germany

Digital Object Identifier: 10.5220/0006176302830293

Proceedings of IVAPP 2017/VISIGRAPP, ISBN: 978-989-758-228-8

Quick Abstract

Nodes in real world networks often have a geographic position. In many cases such as for simulation or optimization, there is a need for non-trivial synthetic geo-located networks. As synthetic datasets are required to have specific properties such as connectivity and geographic distribution, often networks need to be generated. However, their creation is cumbersome if done purely by hand, and inflexible if done fully automated. Here, we present a framework for creating artificial geographic located networks in a visually interactive way. We designed our framework with the what-you-see-is-what-you-get principle in mind, i.e. showing the (intermediate) results of the interactive creation process at any time and allowing the user to adjust the network iteratively. This design allows our system to be also used as a simple viewer for networks that have incomplete location information. Our approach consists of two steps: (1) Creating the network topology and (2) assigning locations to its nodes. Our half automatic system enables the user to easily set the location of the nodes to predefined areas like countries, states, and urban regions, while still being able to flexibly and interactively control the creation process. We show the utility of our system by creating a real-world-like geo-located network.

Related Ontology Subjects/Areas/Topics (5)

Abstract Data Visualization		Graph Visualization		Uncertainty Visualization
Computer Vision, Visualization and Computer Graphics		Spatial Data Visualization

A Novel Implementation Approach for Resource Holons in Reconfigurable Product Manufacturing Cell

Topics: Distributed Control Systems; Autonomous Agents; Industrial Automation and Robotics; Intelligent Design and Manufacturing; Manufacturing Systems Engineering

Authors: Ahmed R. Sadik and Bodo Urban

Affiliation: University of Rostock and Fraunhofer Institute for Computer Graphic Research IGD, Germany

Digital Object Identifier: 10.5220/0005956801300139

Proceedings of ICINCO 2016, ISBN: 978-989-758-198-4

Quick Abstract

Holonic Control Architecture is a successful solution model for reconfigurable manufacturing problems. Two well-known different technologies have been used separately to implement the holonic control model. The first technology is IEC 61499 standard, and the second is autonomous reactive agent. Both of the previous mentioned technologies have its own pros and cons. Therefore this research is merging the two technologies together in one solution body, to magnifying their pros and reduce their cons. Ultimately; it provides a novel implementation model for the manufacturing holons, to be followed in similar reconfigurable manufacturing problems. A human worker in cooperation with a safe industrial robot, has been selected as a case study of a reconfigurable manufacturing problem. The proposed holonic control solution has been applied to the case study, to evaluate the ability of the solution to satisfy the requirements of the case study. The results show the ability of the proposed control solution to provide a flexible physical and logical interaction framework, which can be scaled over more workers in cooperation with more industrial robots.

Related Ontology Subjects/Areas/Topics (9)

Autonomous Agents	Industrial Engineering	Intelligent Design and Manufacturing
Distributed Control Systems	Informatics in Control, Automation and Robotics	Manufacturing Systems Engineering
Industrial Automation and Robotics	Intelligent Control Systems and Optimization	Robotics and Automation

Fuzzy Logic and Multi-biometric Fusion - An Overview

Topics: Biometrics; Fuzzy Logic

Authors: Fabian Maul and Naser Damer

Affiliation: Fraunhofer IGD, Germany

Digital Object Identifier: 10.5220/0005193302180222

Proceedings of ICPRAM 2015, ISBN: 978-989-758-076-5

Quick Abstract

Fuzzy logic has been proposed to improve various aspects of multi-biometric applications including enhancements to the decision making of the application and the robustness to noisy data. This paper discusses recent work that utilized fuzzy logic techniques within the multi-biometric fusion problem. This discussion is presented under two categories, the type of authentication scenario and the nature of the fused data. The paper also presents an introduction to fuzzy logic and multi-biometric fusion. Based on the discussed works, this paper aims to establish current trends and research possibilities in this field.

Related Ontology Subjects/Areas/Topics (11)

Applications	Biometrics and Pattern Recognition	Pattern Recognition
Biomedical Engineering	Fuzzy Logic	Telecommunications
Biomedical Signal Processing	Multimedia	Theory and Methods
Biometrics	Multimedia Signal Processing

Optimization-based Automatic Segmentation of Organic Objects of Similar Types

Topic: Segmentation and Grouping

Authors: Enrico Gutzeit , Martin Radolko , Arjan Kuijper and Uwe von Lukas

Affiliation: Fraunhofer Institute for Computer Research IGD, Germany

Digital Object Identifier: 10.5220/0005314905910598

Proceedings of VISAPP 2015/VISIGRAPP, ISBN: 978-989-758-089-5

Quick Abstract

For the segmentation of multiple objects on unknown background in images, some approaches for specific objects exist. However, no approach is general enough to segment an arbitrary group of organic objects of similar type, like wood logs, apples, or tomatoes. Each approach contains restrictions in the object shape, texture, color or in the image background. Many methods are based on probabilistic inference on Markov Random Fields – summarized in this work as optimization based segmentation. In this paper, we address the automatic segmentation of organic objects of similar types by using optimization based methods. Based on the result of object detection, a fore- and background model is created enabling an automatic segmentation of images. Our novel and more general approach for organic objects is a first and important step in a measuring or inspection system. We evaluate and compare our approaches on images with different organic objects on very different backgrounds, which vary in color and texture. We show that the results are very accurate.

Related Ontology Subjects/Areas/Topics (3)

Computer Vision, Visualization and Computer Graphics

Image and Video Analysis

Segmentation and Grouping

Semi-automatic Analysis of Huge Digital Nautical Charts of Coastal Aerial Images

Topics: Color and Texture Analyses; Shape Representation and Matching; Categorization and Scene Understanding; Document Imaging in Business

Authors: Matthias Vahl , Uwe von Lukas , Bodo Urban and Arjan Kuijper

Affiliation: Fraunhofer IGD, Germany

Digital Object Identifier: 10.5220/0005301501000107

Proceedings of VISAPP 2015/VISIGRAPP, ISBN: 978-989-758-091-8

Quick Abstract

Geo-referenced aerial images are available in very high resolution. The automated production and updating of electronic nautical charts (ENC), as well as other products (e.g. thematic maps), from aerial images is a current challenge for hydrographic organizations. Often standard vision algorithms are not reliable enough for robust object detection in natural images. We thus propose a procedure that combines processing steps on three levels, from pixel (low-level) via segments (mid-level) to semantic information (high level). We combine simple linear iterative clustering (SLIC) as an efficient low-level algorithm with a classification based on texture features by supported vector machine (SVM) and a generalized Hough transformation (GHT) for detecting shapes on mid-level. Finally, we show how semantic information can be used to improve results from the earlier processing steps in the high-level step. As standard vision methods are typically much too slow for such huge-sized images and additionally geographical references must be maintained over the complete procedure, we present a solution to overcome these problems.

Related Ontology Subjects/Areas/Topics (6)

Applications and Services		Computer Vision, Visualization and Computer Graphics		Image and Video Analysis
Color and Texture Analyses		Document Imaging in Business		Shape Representation and Matching

Towards the Deployment of Open Platform AAL Services in Real Life-advantages and Lessons Learned - uSmAAL: A Case Study for Implementing Intelligent AAL Services in Real Life based on the Open Platform universAAL

Topics: Ambient Intelligence; Smart Environments and Housing; Case Studies for AAL

Authors: Jan Stengler , Gouri Gaikward and Helmi Ben Hmida

Affiliation: Fraunhofer Institute for Computer Graphics Research IGD, Germany

Digital Object Identifier: 10.5220/0005450200670074

Proceedings of ICT4AgeingWell 2015, ISBN: 978-989-758-102-1

Quick Abstract

Nowadays, most Ambient Assisted Living systems are confined to individual projects. They are primarily closed products with a limited set of features, thus reducing its extension, adoption and reuse. The aim of this paper is to make a first attempt to increase standardization and interoperability oriented efforts by focusing on open systems. We aim to share our experience with developing and deploying Ambient Assisted Living solutions on the top level of the standardized open platform universAAL in real life. This paper identifies the essential aspects of the system architecture and investigates the advantages of providing generic services, shared and reusable components in real life. In addition, this paper presents an evaluation protocol of the different components, focusing on system sustainability and reliability.

Video Segmentation via a Gaussian Switch Background Model and Higher Order Markov Random Fields

Topic: Segmentation and Grouping

Authors: Martin Radolko and Enrico Gutzeit

Affiliation: Fraunhofer Institute for Computer Research IGD, Germany

Digital Object Identifier: 10.5220/0005308505370544

Proceedings of VISAPP 2015/VISIGRAPP, ISBN: 978-989-758-089-5

Quick Abstract

Foreground-background segmentation in videos is an important low-level task needed for many different applications in computer vision. Therefore, a great variety of different algorithms have been proposed to deal with this problem, however none can deliver satisfactory results in all circumstances. Our approach combines an efficent novel Background Substraction algorithm with a higher order Markov Random Field (MRF) which can model the spatial relations between the pixels of an image far better than a simple pairwise MRF used in most of the state of the art methods. Afterwards, a runtime optimized Belief Propagation algorithm is used to compute an enhanced segmentation based on this model. Lastly, a local between Class Variance method is combined with this to enrich the data from the Background Substraction. To evaluate the results the difficult Wallflower data set is used.

Related Ontology Subjects/Areas/Topics (3)

Computer Vision, Visualization and Computer Graphics

Image and Video Analysis

Segmentation and Grouping

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