Proceedings of the 2009 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

The joint workshop of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Karlsruhe, and the Vision and Fusion Laboratory (Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT)), is organized annually since 2005 with the aim to report on the latest research and development findings of the doctoral students of both institutions. This book provides a collection of 16 technical reports on the research results presented on the 2009 workshop

Proceedings of the 2011 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

This book is a collection of 15 reviewed technical reports summarizing the presentations at the 2011 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. The covered topics include image processing, optical signal processing, visual inspection, pattern recognition and classification, human-machine interaction, world and situation modeling, autonomous system localization and mapping, information fusion, and trust propagation in sensor networks

Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces

This paper contributes to a taxonomy of augmented reality and robotics based on a survey of 460 research papers. Augmented and mixed reality (AR/MR) have emerged as a new way to enhance human-robot interaction (HRI) and robotic interfaces (e.g., actuated and shape-changing interfaces). Recently, an increasing number of studies in HCI, HRI, and robotics have demonstrated how AR enables better interactions between people and robots. However, often research remains focused on individual explorations and key design strategies, and research questions are rarely analyzed systematically. In this paper, we synthesize and categorize this research field in the following dimensions: 1) approaches to augmenting reality; 2) characteristics of robots; 3) purposes and benefits; 4) classification of presented information; 5) design components and strategies for visual augmentation; 6) interaction techniques and modalities; 7) application domains; and 8) evaluation strategies. We formulate key challenges and opportunities to guide and inform future research in AR and robotics

The cockpit for the 21st century

Interactive surfaces are a growing trend in many domains. As one possible manifestation of Mark Weiser’s vision of ubiquitous and disappearing computers in everywhere objects, we see touchsensitive screens in many kinds of devices, such as smartphones, tablet computers and interactive tabletops. More advanced concepts of these have been an active research topic for many years. This has also influenced automotive cockpit development: concept cars and recent market releases show integrated touchscreens, growing in size. To meet the increasing information and interaction needs, interactive surfaces offer context-dependent functionality in combination with a direct input paradigm. However, interfaces in the car need to be operable while driving. Distraction, especially visual distraction from the driving task, can lead to critical situations if the sum of attentional demand emerging from both primary and secondary task overextends the available resources. So far, a touchscreen requires a lot of visual attention since its flat surface does not provide any haptic feedback. There have been approaches to make direct touch interaction accessible while driving for simple tasks. Outside the automotive domain, for example in office environments, concepts for sophisticated handling of large displays have already been introduced. Moreover, technological advances lead to new characteristics for interactive surfaces by enabling arbitrary surface shapes. In cars, two main characteristics for upcoming interactive surfaces are largeness and shape. On the one hand, spatial extension is not only increasing through larger displays, but also by taking objects in the surrounding into account for interaction. On the other hand, the flatness inherent in current screens can be overcome by upcoming technologies, and interactive surfaces can therefore provide haptically distinguishable surfaces. This thesis describes the systematic exploration of large and shaped interactive surfaces and analyzes their potential for interaction while driving. Therefore, different prototypes for each characteristic have been developed and evaluated in test settings suitable for their maturity level. Those prototypes were used to obtain subjective user feedback and objective data, to investigate effects on driving and glance behavior as well as usability and user experience. As a contribution, this thesis provides an analysis of the development of interactive surfaces in the car. Two characteristics, largeness and shape, are identified that can improve the interaction compared to conventional touchscreens. The presented studies show that large interactive surfaces can provide new and improved ways of interaction both in driver-only and driver-passenger situations. Furthermore, studies indicate a positive effect on visual distraction when additional static haptic feedback is provided by shaped interactive surfaces. Overall, various, non-exclusively applicable, interaction concepts prove the potential of interactive surfaces for the use in automotive cockpits, which is expected to be beneficial also in further environments where visual attention needs to be focused on additional tasks.Der Einsatz von interaktiven Oberflächen weitet sich mehr und mehr auf die unterschiedlichsten Lebensbereiche aus. Damit sind sie eine mögliche Ausprägung von Mark Weisers Vision der allgegenwärtigen Computer, die aus unserer direkten Wahrnehmung verschwinden. Bei einer Vielzahl von technischen Geräten des täglichen Lebens, wie Smartphones, Tablets oder interaktiven Tischen, sind berührungsempfindliche Oberflächen bereits heute in Benutzung. Schon seit vielen Jahren arbeiten Forscher an einer Weiterentwicklung der Technik, um ihre Vorteile auch in anderen Bereichen, wie beispielsweise der Interaktion zwischen Mensch und Automobil, nutzbar zu machen. Und das mit Erfolg: Interaktive Benutzeroberflächen werden mittlerweile serienmäßig in vielen Fahrzeugen eingesetzt. Der Einbau von immer größeren, in das Cockpit integrierten Touchscreens in Konzeptfahrzeuge zeigt, dass sich diese Entwicklung weiter in vollem Gange befindet. Interaktive Oberflächen ermöglichen das flexible Anzeigen von kontextsensitiven Inhalten und machen eine direkte Interaktion mit den Bildschirminhalten möglich. Auf diese Weise erfüllen sie die sich wandelnden Informations- und Interaktionsbedürfnisse in besonderem Maße. Beim Einsatz von Bedienschnittstellen im Fahrzeug ist die gefahrlose Benutzbarkeit während der Fahrt von besonderer Bedeutung. Insbesondere visuelle Ablenkung von der Fahraufgabe kann zu kritischen Situationen führen, wenn Primär- und Sekundäraufgaben mehr als die insgesamt verfügbare Aufmerksamkeit des Fahrers beanspruchen. Herkömmliche Touchscreens stellen dem Fahrer bisher lediglich eine flache Oberfläche bereit, die keinerlei haptische Rückmeldung bietet, weshalb deren Bedienung besonders viel visuelle Aufmerksamkeit erfordert. Verschiedene Ansätze ermöglichen dem Fahrer, direkte Touchinteraktion für einfache Aufgaben während der Fahrt zu nutzen. Außerhalb der Automobilindustrie, zum Beispiel für Büroarbeitsplätze, wurden bereits verschiedene Konzepte für eine komplexere Bedienung großer Bildschirme vorgestellt. Darüber hinaus führt der technologische Fortschritt zu neuen möglichen Ausprägungen interaktiver Oberflächen und erlaubt, diese beliebig zu formen. Für die nächste Generation von interaktiven Oberflächen im Fahrzeug wird vor allem an der Modifikation der Kategorien Größe und Form gearbeitet. Die Bedienschnittstelle wird nicht nur durch größere Bildschirme erweitert, sondern auch dadurch, dass Objekte wie Dekorleisten in die Interaktion einbezogen werden können. Andererseits heben aktuelle Technologieentwicklungen die Restriktion auf flache Oberflächen auf, so dass Touchscreens künftig ertastbare Strukturen aufweisen können. Diese Dissertation beschreibt die systematische Untersuchung großer und nicht-flacher interaktiver Oberflächen und analysiert ihr Potential für die Interaktion während der Fahrt. Dazu wurden für jede Charakteristik verschiedene Prototypen entwickelt und in Testumgebungen entsprechend ihres Reifegrads evaluiert. Auf diese Weise konnten subjektives Nutzerfeedback und objektive Daten erhoben, und die Effekte auf Fahr- und Blickverhalten sowie Nutzbarkeit untersucht werden. Diese Dissertation leistet den Beitrag einer Analyse der Entwicklung von interaktiven Oberflächen im Automobilbereich. Weiterhin werden die Aspekte Größe und Form untersucht, um mit ihrer Hilfe die Interaktion im Vergleich zu herkömmlichen Touchscreens zu verbessern. Die durchgeführten Studien belegen, dass große Flächen neue und verbesserte Bedienmöglichkeiten bieten können. Außerdem zeigt sich ein positiver Effekt auf die visuelle Ablenkung, wenn zusätzliches statisches, haptisches Feedback durch nicht-flache Oberflächen bereitgestellt wird. Zusammenfassend zeigen verschiedene, untereinander kombinierbare Interaktionskonzepte das Potential interaktiver Oberflächen für den automotiven Einsatz. Zudem können die Ergebnisse auch in anderen Bereichen Anwendung finden, in denen visuelle Aufmerksamkeit für andere Aufgaben benötigt wird

Image Retrieval within Augmented Reality

Die vorliegende Arbeit untersucht das Potenzial von Augmented Reality zur Verbesserung von Image Retrieval Prozessen. Herausforderungen in Design und Gebrauchstauglichkeit wurden für beide Forschungsbereiche dargelegt und genutzt, um Designziele für Konzepte zu entwerfen. Eine Taxonomie für Image Retrieval in Augmented Reality wurde basierend auf der Forschungsarbeit entworfen und eingesetzt, um verwandte Arbeiten und generelle Ideen für Interaktionsmöglichkeiten zu strukturieren. Basierend auf der Taxonomie wurden Anwendungsszenarien als weitere Anforderungen für Konzepte formuliert. Mit Hilfe der generellen Ideen und Anforderungen wurden zwei umfassende Konzepte für Image Retrieval in Augmented Reality ausgearbeitet. Eins der Konzepte wurde auf einer Microsoft HoloLens umgesetzt und in einer Nutzerstudie evaluiert. Die Studie zeigt, dass das Konzept grundsätzlich positiv aufgenommen wurde und bietet Erkenntnisse über unterschiedliches Verhalten im Raum und verschiedene Suchstrategien bei der Durchführung von Image Retrieval in der erweiterten Realität.:1 Introduction 1.1 Motivation and Problem Statement 1.1.1 Augmented Reality and Head-Mounted Displays 1.1.2 Image Retrieval 1.1.3 Image Retrieval within Augmented Reality 1.2 Thesis Structure 2 Foundations of Image Retrieval and Augmented Reality 2.1 Foundations of Image Retrieval 2.1.1 Definition of Image Retrieval 2.1.2 Classification of Image Retrieval Systems 2.1.3 Design and Usability in Image Retrieval 2.2 Foundations of Augmented Reality 2.2.1 Definition of Augmented Reality 2.2.2 Augmented Reality Design and Usability 2.3 Taxonomy for Image Retrieval within Augmented Reality 2.3.1 Session Parameters 2.3.2 Interaction Process 2.3.3 Summary of the Taxonomy 3 Concepts for Image Retrieval within Augmented Reality 3.1 Related Work 3.1.1 Natural Query Specification 3.1.2 Situated Result Visualization 3.1.3 3D Result Interaction 3.1.4 Summary of Related Work 3.2 Basic Interaction Concepts for Image Retrieval in Augmented Reality 3.2.1 Natural Query Specification 3.2.2 Situated Result Visualization 3.2.3 3D Result Interaction 3.3 Requirements for Comprehensive Concepts 3.3.1 Design Goals 3.3.2 Application Scenarios 3.4 Comprehensive Concepts 3.4.1 Tangible Query Workbench 3.4.2 Situated Photograph Queries 3.4.3 Conformance of Concept Requirements 4 Prototypic Implementation of Situated Photograph Queries 4.1 Implementation Design 4.1.1 Implementation Process 4.1.2 Structure of the Implementation 4.2 Developer and User Manual 4.2.1 Setup of the Prototype 4.2.2 Usage of the Prototype 4.3 Discussion of the Prototype 5 Evaluation of Prototype and Concept by User Study 5.1 Design of the User Study 5.1.1 Usability Testing 5.1.2 Questionnaire 5.2 Results 5.2.1 Logging of User Behavior 5.2.2 Rating through Likert Scales 5.2.3 Free Text Answers and Remarks during the Study 5.2.4 Observations during the Study 5.2.5 Discussion of Results 6 Conclusion 6.1 Summary of the Present Work 6.2 Outlook on Further WorkThe present work investigates the potential of augmented reality for improving the image retrieval process. Design and usability challenges were identified for both fields of research in order to formulate design goals for the development of concepts. A taxonomy for image retrieval within augmented reality was elaborated based on research work and used to structure related work and basic ideas for interaction. Based on the taxonomy, application scenarios were formulated as further requirements for concepts. Using the basic interaction ideas and the requirements, two comprehensive concepts for image retrieval within augmented reality were elaborated. One of the concepts was implemented using a Microsoft HoloLens and evaluated in a user study. The study showed that the concept was rated generally positive by the users and provided insight in different spatial behavior and search strategies when practicing image retrieval in augmented reality.:1 Introduction 1.1 Motivation and Problem Statement 1.1.1 Augmented Reality and Head-Mounted Displays 1.1.2 Image Retrieval 1.1.3 Image Retrieval within Augmented Reality 1.2 Thesis Structure 2 Foundations of Image Retrieval and Augmented Reality 2.1 Foundations of Image Retrieval 2.1.1 Definition of Image Retrieval 2.1.2 Classification of Image Retrieval Systems 2.1.3 Design and Usability in Image Retrieval 2.2 Foundations of Augmented Reality 2.2.1 Definition of Augmented Reality 2.2.2 Augmented Reality Design and Usability 2.3 Taxonomy for Image Retrieval within Augmented Reality 2.3.1 Session Parameters 2.3.2 Interaction Process 2.3.3 Summary of the Taxonomy 3 Concepts for Image Retrieval within Augmented Reality 3.1 Related Work 3.1.1 Natural Query Specification 3.1.2 Situated Result Visualization 3.1.3 3D Result Interaction 3.1.4 Summary of Related Work 3.2 Basic Interaction Concepts for Image Retrieval in Augmented Reality 3.2.1 Natural Query Specification 3.2.2 Situated Result Visualization 3.2.3 3D Result Interaction 3.3 Requirements for Comprehensive Concepts 3.3.1 Design Goals 3.3.2 Application Scenarios 3.4 Comprehensive Concepts 3.4.1 Tangible Query Workbench 3.4.2 Situated Photograph Queries 3.4.3 Conformance of Concept Requirements 4 Prototypic Implementation of Situated Photograph Queries 4.1 Implementation Design 4.1.1 Implementation Process 4.1.2 Structure of the Implementation 4.2 Developer and User Manual 4.2.1 Setup of the Prototype 4.2.2 Usage of the Prototype 4.3 Discussion of the Prototype 5 Evaluation of Prototype and Concept by User Study 5.1 Design of the User Study 5.1.1 Usability Testing 5.1.2 Questionnaire 5.2 Results 5.2.1 Logging of User Behavior 5.2.2 Rating through Likert Scales 5.2.3 Free Text Answers and Remarks during the Study 5.2.4 Observations during the Study 5.2.5 Discussion of Results 6 Conclusion 6.1 Summary of the Present Work 6.2 Outlook on Further Wor

Attention and Anticipation in Fast Visual-Inertial Navigation

We study a Visual-Inertial Navigation (VIN) problem in which a robot needs to estimate its state using an on-board camera and an inertial sensor, without any prior knowledge of the external environment. We consider the case in which the robot can allocate limited resources to VIN, due to tight computational constraints. Therefore, we answer the following question: under limited resources, what are the most relevant visual cues to maximize the performance of visual-inertial navigation? Our approach has four key ingredients. First, it is task-driven, in that the selection of the visual cues is guided by a metric quantifying the VIN performance. Second, it exploits the notion of anticipation, since it uses a simplified model for forward-simulation of robot dynamics, predicting the utility of a set of visual cues over a future time horizon. Third, it is efficient and easy to implement, since it leads to a greedy algorithm for the selection of the most relevant visual cues. Fourth, it provides formal performance guarantees: we leverage submodularity to prove that the greedy selection cannot be far from the optimal (combinatorial) selection. Simulations and real experiments on agile drones show that our approach ensures state-of-the-art VIN performance while maintaining a lean processing time. In the easy scenarios, our approach outperforms appearance-based feature selection in terms of localization errors. In the most challenging scenarios, it enables accurate visual-inertial navigation while appearance-based feature selection fails to track robot's motion during aggressive maneuvers.Comment: 20 pages, 7 figures, 2 table