TY - BOOK A1 - Beneken, Gerd A1 - Ernst, H. A1 - Schmidt, Jochen T1 - Grundkurs Informatik: Grundlagen und Konzepte für die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einführung (Auflage von 2015) N2 - Das Buch bietet eine umfassende und praxisorientierte Einführung in die wesentlichen Grundlagen und Konzepte der Informatik. Es umfasst den Stoff, der typischerweise in den ersten Semestern eines Informatikstudiums vermittelt wird, vertieft Zusammenhänge, die darüber hinausgehen und macht sie verständlich. Die Themenauswahl orientiert sich an der langfristigen Relevanz für die praktische Anwendung. Praxisnah und aktuell werden die Inhalte für Studierende der Informatik und verwandter Studiengänge sowie für im Beruf stehende Praktiker vermittelt. Die vorliegende fünfte Auflage wurde grundlegend überarbeitet und aktualisiert. KW - Informatik KW - Lehrbuch KW - IT- Praxis Y1 - 2015 PB - Springer Vieweg CY - Berlin ER - TY - CHAP A1 - Wenninger, Marc A1 - Schmidt, Jochen A1 - Goeller, Toni T1 - Appliance Usage Prediction for the Smart Home with an Application to Energy Demand Side Management - And Why Accuracy is not a Good Performance Metric for this Problem. T2 - 6th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS) N2 - Shifting energy peak load is a subject that plays a huge role in the currently changing energy market, where renewable energy sources no longer produce the exact amount of energy demanded. Matching demand to supply requires behavior Changes on the customerside, which can be achieved by incentives suchas Real-Time-Pricing (RTP). Various studies show that such incentives cannot be utilized without a complexity reduction, e.g., by smart home automation systems that inform the customer about possible savings or automatically schedule appliances to off-peak load phases. We propose a probabilistic appliance usage prediction based on historical energy data that can be used to identify the times of day where an appliance will be used and therefore make load shift recommendations that suite the customer’s usage profile. A huge issue is how to provide a valid performance evaluation for this particular problem. We will argue why the commonly used accuracy metric is not suitable, and suggest to use other metrics like the area under the Receiver Operating Characteristic (ROC) curve, Matthews Correlation Coefficient (MCC) or F1-Score instead. KW - Real Time Pricing (RTP) KW - Household Appliance Usage Prediction KW - Demand Side Management Y1 - 2017 ER - TY - CHAP A1 - Goeller, Toni A1 - Wenninger, Marc A1 - Schmidt, Jochen T1 - Towards Cost-Effective Utility Business Models - Selecting a Communication Architecture for the Rollout of New Smart Energy Services T2 - Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS N2 - The IT architecture for meter reading and utility services is at the core of new business models and has a decisive role as an enabler for resource efficiency measures. The communication architecture used by those services has significant impact on cost, flexibility and speed of new service rollout. This article describes how the dominant system model for meter reading came about, what alternative models exist, and what trade-offs those models have for rollout of new services by different stakeholders. Control of a self learning home automation system by dynamic tariff information (Real-Time-Pricing) is given as an application example. KW - Smart Meter, Advanced Metering Infrastructure, AMI Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:861-opus4-8332 SN - 978-989-758-292-9 SP - 231 EP - 237 PB - SciTePress ER - TY - BOOK A1 - Ernst, Hartmut A1 - Schmidt, Jochen A1 - Beneken, Gerd T1 - Grundkurs Informatik: Grundlagen und Konzepte für die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einführung N2 - Zahlensysteme und binäre Arithmetik – Nachricht und Information – Codierung und Datenkompression – Verschlüsselung – Schaltalgebra, Schaltnetze und Elemente der Computerhardware – Rechnerarchitekturen – Rechnernetze – Betriebssysteme – prozedurale und objektorientierte Programmierung (C und Java) – Automatentheorie und formale Sprachen – Berechenbarkeit und Komplexität – Suchen und Sortieren – Bäume und Graphen – Software-Engineering – Datenbanken – Anwendungsprogrammierung im Internet (HTML, CSS, JavaScript und PHP) – Deep Learning mit neuronalen Netzen KW - Grundlagen Informatik Y1 - 2020 SN - 978-3-658-30330-3 PB - Springer Vieweg CY - Wiesbaden ET - 7 ER - TY - BOOK A1 - Schmidt, Jochen T1 - Grundkurs Informatik - Das Übungsbuch: 148 Aufgaben mit Lösungen KW - Grundlagen Informatik Übungen Y1 - 2020 SN - 978-3-658-30332-7 PB - Springer Vieweg CY - Wiesbaden ET - 2 ER - TY - JOUR A1 - Wenninger, Marc A1 - Maier, Andreas A1 - Schmidt, Jochen T1 - DEDDIAG, a domestic electricity demand dataset of individual appliances in Germany JF - Scientific Data N2 - Real-world domestic electricity demand datasets are the key enabler for developing and evaluating machine learning algorithms that facilitate the analysis of demand attribution and usage behavior. Breaking down the electricity demand of domestic households is seen as the key technology for intelligent smart-grid management systems that seek an equilibrium of electricity supply and demand. For the purpose of comparable research, we publish DEDDIAG, a domestic electricity demand dataset of individual appliances in Germany. The dataset contains recordings of 15 homes over a period of up to 3.5 years, wherein total 50 appliances have been recorded at a frequency of 1 Hz. Recorded appliances are of significance for load-shifting purposes such as dishwashers, washing machines and refrigerators. One home also includes three-phase mains readings that can be used for disaggregation tasks. Additionally, DEDDIAG contains manual ground truth event annotations for 14 appliances, that provide precise start and stop timestamps. Such annotations have not been published for any long-term electricity dataset we are aware of. KW - Machine Learning Y1 - 2021 UR - https://doi.org/10.1038/s41597-021-00963-2 VL - 8 IS - 176 ER - TY - CHAP A1 - Bayerl, Sebastian P. A1 - Wenninger, Marc A1 - Schmidt, Jochen A1 - Wolff von Gudenberg, Alexander A1 - Riedhammer, Korbinian T1 - STAN: A stuttering therapy analysis helper T2 - 2021 IEEE Spoken Language Technology Workshop (SLT) N2 - Stuttering is a complex speech disorder identified by repetitions, prolongations of sounds, syllables or words and blockswhile speaking. Specific stuttering behaviour differs strongly,thus needing personalized therapy. Therapy sessions requirea high level of concentration by the therapist. We introduce STAN, a system to aid speech therapists in stuttering therapysessions. Such an automated feedback system can lower the cognitive load on the therapist and thereby enable a more consistent therapy as well as allowing analysis of stuttering over the span of multiple therapy sessions. KW - Machine Learning Y1 - 2021 ER - TY - CHAP A1 - Wenninger, Marc A1 - Bayerl, Sebastian P. A1 - Maier, Andreas A1 - Schmidt, Jochen T1 - Recurrence Plot Spacial Pyramid Pooling Network for Appliance Identification in Non-Intrusive Load Monitoring T2 - 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) N2 - Parameter free Non-intrusive Load Monitoring (NILM) algorithms are a major step toward real-world NILM scenarios. The identification of appliances is the key element in NILM. The task consists of identification of the appliance category and its current state. In this paper, we present a param- eter free appliance identification algorithm for NILM using a 2D representation of time series known as unthresholded Recurrence Plots (RP) for appliance category identification. One cycle of voltage and current (V-I trajectory) are transformed into a RP and classified using a Spacial Pyramid Pooling Convolutional Neural Network architecture. The performance of our approach is evaluated on the three public datasets COOLL, PLAID and WHITEDv1.1 and compared to previous publications. We show that compared to other approaches using our architecture no initial parameters have to be manually tuned for each specific dataset. KW - NILM KW - V-I trajectory KW - Recurrence Plot Y1 - 2021 UR - https://doi.org/10.1109/ICMLA52953.2021.00025 SP - 108 EP - 115 ER - TY - CHAP A1 - Zinßer, T. A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Performance Analysis of Nearest Neighbor Algorithms for ICP Registration of 3-D Point Sets T2 - Vision, Modeling, and Visualization 2003 N2 - There are many nearest neighbor algorithms tailor made for ICP,but most of them require Special input data like range Images or triangle meshes. We focus on efficient nearest neighbor algorithms that do not impose this limitation, and thus can also be used with 3-D point sets generated by structure-frommotion techniques. We shortly present the evaluated algorithms and introduce the modifications we made to improve their efficiency. In particular, several enhancements to the well-known k-D tree algorithm are described. The first part of our Performance Analysis consists of Experiments on synthetic point sets, whereas the second part features experiments with the ICP algorithm on real point sets. Both parts are completed by a thorough evaluation of the obtained results. KW - ICP Algorithm KW - 3D Point-Sets Y1 - 2003 ER - TY - JOUR A1 - Zobel, M. A1 - Denzler, J. A1 - Heigl, B. A1 - Nöth, E. A1 - Paulus, D. A1 - Schmidt, Jochen A1 - Stemmer, G. T1 - MOBSY: Integration of vision and dialogue in service robots JF - Machine Vision and Applications N2 - This contribution introduces MOBSY, a fully integrated, autonomous mobile service robot system. It acts as an automatic dialogue-based receptionist for visitors to our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. The techniques involved range from computer vision over speech understanding to classical robotics. Along with the two main aspects of vision and speech, we also focus on the integration aspect, both on the methodological and on the technical level. We describe the task and the techniques involved. Finally, we discuss the experiences that we gained with MOBSY during a live performance at our institute. KW - Service robots KW - Computer vision KW - Speech understanding and dialogue KW - Integrated System Y1 - 2003 ER - TY - CHAP A1 - Wenhardt, S. A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Didaktische Aufbereitung von Methoden des Rechnersehens für virtuelle Vorlesungen T2 - Forschungsbeiträge zur Didaktik der Informatik - Theorie, Praxis, Evaluation N2 - Dieser Artikel stellt ein Konzept f¨ur eine Online-Vorlesung im Rahmen der virtuellen Hochschule Bayern vor. Zunächst werden kurz die fachlichen Inhalte erl¨autert, die es zu vermitteln gilt. Nach dieser Einführung wird auf die Umsetzung der Inhalte in eine dem neuen Medium Internet angemessene Form eingegangen. Dies betrifft vor allem die ausgewählten Techniken, die zur Wissensvermittlung eingesetzt werden. Ein besonderer Schwerpunkt liegt auf der Möglichkeit durch Interaktivität das Wissen experimentell zu vertiefen und somit eine Verbindung zwischen dem theoretisch Gelernten und dem praktisch Erfahrenen herzustellen. Weiterhin wird eine Vielfalt an Kommunikationsm¨oglichkeiten vorgestellt, da Kommunikation eine wichtige soziale Komponente im Lernprozess und h¨aufig entscheidend f¨ur den Erfolg ist. KW - Rechnersehen KW - virtuelle Vorlesung KW - Didaktik Y1 - 2002 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Vogt, F. A1 - Niemann, H. T1 - Nonlinear Refinement of Camera Parameters using an Endoscopic Surgery Robot T2 - Proceedings of IAPR Conference on Machine Vision Applications (MVA) N2 - We present an Approach for non linea roptimization of the parameters of an endoscopic camera mounted on a surgery robot. The goal is to generate a depth map for each image in order to enhance the quality of medical light fields. The pose information provided by the robot is used as an initialization, where especially the orientation isi naccurate. Refinement of intrinsic and extrinsic camera parameters is performed by minimizing the back-projectionerror of 3-D points that are reconstructed by triangulation from image Feature stracked over an image sequence. Optimization of the camera parameters results in an enhancement of Rendering Quality in two ways: More accurate parameters lead to better interpolation as well as to better depth maps for approximating the scenegeometry. KW - Endoscopic Surgery Robot KW - endoscopic camera KW - minimalinvasive surgery Y1 - 2018 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Niemann, H. A1 - Vogt, F. T1 - Dense Disparity Maps in Real-Time with an Application to Augmented Reality T2 - Proceedings Sixth IEEE Workshop on Applications of Computer Vision (WACV 2002), pages 225-230, Orlando, FL USA N2 - This work presents a technique for computing dense disparity maps from a binocular stereo camera system. The methods are applied in an Augmented Reality setting for combining real and virtual worlds with proper occlusions. The proposed stereo correspondence technique is based oil area matching and facilitates an efficient strategy by using the concept of a three-dimensional similarity accumulator whereby occlusions are detected and object boundaries are extracted correctly. The main contribution of this paper is the way we fill the accumulator using absolute differences of images and computing a mean filter on these difference images. This. is. where the main advantages of the accumulator approach can be exploited, since all entries can be computed in parallel and thus extremely efficient. Additionally, we-perform an asymmetric correction step and a post-processing of the disparity maps that maintains object edges. KW - Augmented Reality (AR) KW - Layout KW - Camera KW - Real time systems Y1 - 2018 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Using Quaternions for Parametrizing 3D Rotations in Unconstrained Nonlinear Optimization T2 - Vision, Modeling, and Visualization 2001, pages 399-406, Stuttgart, Germany N2 - In this paper we address the problem of using quaternions in unconstrained nonlinear optimization of 3-D rotations. Quaternions representing rotations have four elements but only three degrees of freedom, since they must be of norm one. This constraint has to be taken into account when applying e.g. the Levenberg-Marquardt algorithm, a method for unconstrained nonlinear optimization widely used in computer vision. We propose an easy to use method for achieving this. Experiments using our parametrization in photo grammetric bündle -adjustment are presented at the end of the paper. KW - 3D Rotations KW - Pattern recognition KW - Unconstrained NonlinearOptimization Y1 - 2002 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Scholz, I. A1 - Niemann, H. T1 - Placing Arbitrary Objects in a Real Scene Using a Color Cube for Pose Estimation T2 - Pattern Recognition, 23rd DAGM Symposium N2 - We describe an Augmented Reality system using the corners of a color cube for camera calibration. In the augmented image the cube is replaced by a computer generated virtual object. The cube is localized in an image by the CSC color segmentation algorithm. The camera projection matrix is estimated with a linear method that is followed by a nonlinear refinement step. Because of possible missclassifications of the segmented color regions and the minimum number of point correspondences used for calibration, the estimated pose of the cube may be very erroneous for some frames; therefore we perform outlier detection and treatment for rendering the virtual object in an acceptable manner. KW - Augmented Reality (AR) KW - Camera calibration KW - Color segmentation Y1 - 2001 ER - TY - CHAP A1 - Scholz, I. A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Farbbildverarbeitung unter Echtzeitbedingungen in der Augmented Reality T2 - Workshop Farbbildverarbeitung, pages 59-65, Erlangen, Germany, 4.-5. Oktober 2001. Universität Erlangen-Nürnberg, Institut für Informatik N2 - Es wird ein System aus der Augmented Reality (Erweiterte Realiäat, AR) vorgestellt, das zur Kamerakalibrierung einen farbigen Würfel verwendet, der außerdem als Platzhalter für ein virtuelles Objekt dient. Zur Erkennung des Würfels in einer Szene werden Methoden aus der Farbbildverarbeitung verwendet, wie der Color Structure Code (CSC) und die Klassifikation der entstehenden Regionen nach ihrer Farbe. Zur Beschleunigung der Segmentierung wird ein hierarchisches Verfahren eingesetzt. KW - Augmented Reality (AR) KW - Farbsegmentierung Y1 - 2001 ER - TY - JOUR A1 - Zobel, M. A1 - Denzler, J. A1 - Heigl, B. A1 - Nöth, E. A1 - Paulus, D. A1 - Schmidt, Jochen A1 - Stemmer, G. T1 - Demonstration von Bildverarbeitung und Sprachverstehen in der Dienstleistungsrobotik JF - Autonome Mobile Systeme N2 - Die typischerweise gewünschten Einsatzgebiete für Dienstleistungsroboter, z. B. Krankenhäuser oder Seniorenheime, stellen sehr hohe Anforderungen an die Mensch-Maschine-Schnittstelle. Diese Erfordernisse gehen im Allgemeinen über die Möglichkeiten der Standardsensoren, wie Ultraschalloder Infrarotsensoren, hinaus. Es müssen daher ergänzende Verfahren zum Einsatz kommen. Aus der Sicht der Mustererkennung sind die Nutzung des Rechnersehens und des natürlichsprachlichen Dialogs von besonderem Interesse. Dieser Beitrag stellt das mobile System MOBS Y vor. MOBS Y ist ein vollkommen integrierter autonomer mobiler Dienstleistungsroboter. Er dient als ein automatischer dialogbasierter Empfangsservice für Besucher unseres Instituts. MOBSY vereinigt vielfältige Methoden aus unterschiedlichsten Forschungsgebieten in einem eigenständigen System. Die zum Einsatz kommenden Methoden aus dem Bereich der Bildverarbeitung reichen dabei von Objektklassifikation über visuelle Selbstlokalisierung und Rekalibrierung bis hin zu multiokularer Objektverfolgung. Die Dialogkomponente umfasst Methoden der Spracherkennung, des Sprachverstehens und die Generierung von Antworten. Im Beitrag werden die zu erfüllende Aufgabe und die einzelnen Verfahren dargestellt. KW - Dienstleistungsroboter KW - multiokulare Objektverfolgung KW - Spracherkennung KW - Sensorik bei Robotern Y1 - 2001 ER - TY - CHAP A1 - Zobel, M. A1 - Denzler, J. A1 - Heigl, B. A1 - Nöth, E. A1 - Paulus, D. A1 - Schmidt, Jochen A1 - Stemmer, G. T1 - MOBSY: Integration of vision and dialogue in service robots T2 - Computer Vision Systems, Proceedings Second International Workshop, ICVS 2001, Vancouver, Canada N2 - MOBSY is a fully integrated autonomous mobile service robot system. It acts as an automatic dialogue based receptionist for visitors of our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. Especially the computer vision and dialogue aspects are of main interest from the pattern recognition’s point of view. To summarize shortly, the involved techniques range from object classification over visual self-localization and recalibration to object tracking with multiple cameras. A dialogue component has to deal with speech recognition, understanding and answer generation. Further techniques needed are navigation, obstacle avoidance, and mechanisms to provide fault tolerant behavior. This contribution introduces our mobile system MOBSY. Among the main aspects vision and speech, we focus also on the integration aspect, both on the methodological and on the technical level. We describe the task and the involved techniques. Finally, we discuss the experiences that we gained with MOBSY during a live performance at the 25th anniversary of our institute KW - Speech recognition KW - Obstacle Avoidance  KW - Humanoid Robot  KW - Service Robot Y1 - 2001 ER - TY - BOOK A1 - Ernst, H. A1 - Schmidt, Jochen A1 - Beneken, Gerd T1 - Grundkurs Informatik: Grundlagen und Konzepte für die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einführung N2 - Zahlensysteme und binäre Arithmetik Nachricht und Information Codierung und Datenkompression Verschlüsselung Schaltalgebra, Schaltnetze und Elemente der Computerhardware Rechnerarchitekturen Rechnernetze Betriebssysteme Datenbanken Automatentheorie und formale Sprachen Berechenbarkeit und Komplexität Suchen und Sortieren Bäume und Graphen prozedurale und objektorientierte Programmierung (C und Java) Anwendungsprogrammierung im Internet (HTML, CSS, JavaScript und PHP) Software-Engineering KW - Informatik KW - Anwendungsprogrammierung im Internet Y1 - 2016 PB - Springer Vieweg CY - Berlin ER - TY - CHAP A1 - Zenger, A. A1 - Schmidt, Jochen A1 - Krödel, M. T1 - Towards the Intelligent Home: Using Reinforcement-Learning for Optimal Heating Control T2 - Advances in Artificial Intelligence, Proceedings of the 36th Annual Conference on AI, volume 8077 of Lecture Notes in Artificial Intelligence N2 - We propose a reinforcement learning approach to heating control in home automation, that can acquire a set of rules enabling an agent to heat a room to the desired temperature at a defined time while conserving as much energy as possible. Experimental results are presented that show the feasibility of our method. KW - Target Temperature KW - Reward Function KW - Heating control KW - Home Automation KW - Approximate dynamic program Y1 - 2013 PB - Springer ER - TY - JOUR A1 - Darms, M. A1 - Fölster, F. A1 - Schmidt, Jochen A1 - Fröhlich, D. A1 - Eckert, A. T1 - Data Fusion Strategies in Advanced Driver Assistance Systems JF - SAE International Journal of Passenger Cars – Electronic and Electrical Systems N2 - Data fusion plays a central role in more and more automotive applications, especially for driver assistance systems. On the one hand the process of data fusion combines data and information to estimate or predict states of observed objects. On the other hand data fusion introduces abstraction layers for data description and allows building more flexible and modular systems.The data fusion process can be divided into a low-level processing (tracking and object discrimination) and a high level processing (situation assessment). High level processing becomes more and more the focus of current research as different assistance applications will be combined into one comprehensive assistance system. Different levels/strategies for data fusion can be distinguished: Fusion on raw data level, fusion on feature level and fusion on decision level. All fusion strategies can be found in current driver assistance implementations. The paper gives an overview of the different fusion strategies and shows their application in current driver assistance systems. For low level processing a raw data fusion approach in a stereo video system is described, as an example for feature level fusion the fusion of radar and camera data for tracking is explained. As an example for a high level fusion algorithm an approach for a situation assessment based on multiple sensors is given. The paper describes practical realizations of these examples and points out their potential to further increase traffic safety with reasonably low cost for the overall system. KW - Driver Assistent Systems KW - Data Fusion KW - automotive applications Y1 - 2010 ER - TY - CHAP A1 - Wong, C.K. A1 - Yeap, W.K. A1 - Schmidt, Jochen T1 - Our Next Generation of Robotics Researchers? Teaching Robotics at Primary School Level. T2 - Readings in Technology and Education: Proceedings of International Conference on Information Communication Technologies in Education N2 - In this paper, we present our experience in designing and teaching of our first robotics course for students at primary school level. The course was carried out over a comparatively short period of time, namely 6 weeks, 2 hours per week. In contrast to many other projects, we use robots that researchers used to conduct their research and discuss problems faced by these researchers. Thus, this is not a behavioural study but a hands-on learning experience for the students. The aim is to highlight the development of autonomous robots and artificial intelligence as well as to promote science and robotics in schools. KW - Robotic Research KW - Teaching Robotics KW - Software Development Y1 - 2009 ER - TY - JOUR A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Data Selection for Hand-eye Calibration: A Vector Quantization Approach JF - The International Journal of Robotics Research N2 - This paper presents new vector quantization based methods for selecting well-suited data for hand-eye calibration from a given sequence of hand and eye movements. Data selection can improve the accuracy of classic hand-eye calibration, and make it possible in the first place in situations where the standard approach of manually selecting positions is inconvenient or even impossible, especially when using continuously recorded data. A variety of methods is proposed, which differ from each other in the dimensionality of the vector quantization compared to the degrees of freedom of the rotation representation, and how the rotation angle is incorporated. The performance of the proposed vector quantization based data selection methods is evaluated using data obtained from a manually moved optical tracking system (hand) and an endoscopic camera (eye). KW - hand- eye calibration KW - vektor quantization Y1 - 2018 ER - TY - CHAP A1 - Yeap, W.K. A1 - Wong, C.K. A1 - Schmidt, Jochen T1 - Using a Mobile Robot to Test a Theory of Cognitive Mapping. T2 - Robotics and Cognitive Approaches to Spatial Mapping, Springer Tracts in Advanced Robotics N2 - This paper describes using a mobile robot, equipped with some sonar sensors and an odometer, to test navigation through the use of a cognitive map. The robot explores an office environment, computes a cognitive map, which is a network of ASRs [36, 35], and attempts to find its way home. Ten trials were conducted and the robot found its way home each time. From four random positions in two trials, the robot estimated the home position relative to its current position reasonably accurately. Our robot does not solve the simultaneous localization and mapping problem and the map computed is fuzzy and inaccurate with much of the details missing. In each homeward journey, it computes a new cognitive map of the same part of the environment, as seen from the perspective of the homeward journey. We show how the robot uses distance information from both maps to find its way home. KW - Cognitive Mapping KW - Mobile Robot KW - Simultaneous Localization  Y1 - 2008 PB - Springer CY - Berlin ER - TY - CHAP A1 - Schmidt, Jochen A1 - Wong, C.K. A1 - Yeap, W.K. T1 - Spatial Information Extraction for Cognitive Mapping with a Mobile Robot. T2 - Conference on Spatial Information Theory: COSIT'07, Melbourne, Australia. Volume 4736 of Lecture Notes in Computer Science N2 - When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home. Humans naturally use more powerful heuristics while lower animals have shown to develop a variety of methods that tend to utilize two key pieces of information, namely distance and orientation information. Their methods differ depending on how they sense their environment. Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting “cognitive map” be used for localization? In this paper, we present an approach using a mobile robot to generate a “cognitive map”, the main focus being on experiments conducted in large spaces that the robot cannot apprehend at once due to the very limited range of its sensors. The robot computes a “cognitive map” and uses distance and orientation information for localization. KW - Mobile Robot KW - Sonar Sensor KW - Robotic Research Y1 - 2018 ER - TY - JOUR A1 - Schmidt, Jochen A1 - Wong, C.K. A1 - Yeap, W.K. T1 - Localisation and Mapping with a Mobile Robot Using Sparse Range Data JF - Autonomous Robots and Agents, Studies in Computational Intelligence (SCI), N2 - We present an approach for indoor mapping and localisation using sparse range data, acquired by a mobile robot equipped with sonar sensors. The chapter consists of two main parts. First, a split and merge based method for dividing a given metric map into distinct regions is presented, thus creating a topological map in a metric framework. Spatial information extracted from this map is then used for self-localisation on the return home journey. The robot computes local confidence maps for two simple localisation strategies based on distance and relative orientation of regions. These local maps are then fused to produce overall confidence maps. KW - Mobile Robot KW - Sonar Sensor KW - Sensor Data Fusion KW - Robotic Research Y1 - 2007 PB - Springer ER - TY - CHAP A1 - Wong, C.K. A1 - Yeap, W.K. A1 - Schmidt, Jochen T1 - Using a Mobile Robot for Cognitive Mapping T2 - International Joint Conference on Artificial Intelligence (IJCAI), pages 2243-2248, Hyderabad, India, 2007 N2 - When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home. Humans naturally use more powerful heuristics while lower animals have shown to developa varietyof methodsthat tend to utilize two key pieces of information,namely distance and orientation information. Their methods differ depending on how they sense their environment. Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting “cognitive map” be used to return home? In this paper, we presented a novel approach using a mobile robot to do cognitive mapping. Our robot computes a “cognitive map” and uses distance and orientation information to find its way home. The process developed provides interesting insights into the nature of cognitive mapping and encourages us to use a mobile robot to do cognitive mapping in the future, as opposed to its popular use in robot mapping. KW - Cognitive Mapping KW - Sonar Sensor KW - Robotic Research Y1 - 2007 ER - TY - BOOK A1 - Schmidt, Jochen T1 - 3-D Reconstruction and Stereo Self-Calibration for Augmented Reality N2 - The main focus of this work is the development of new methods for the self-calibration of a rigid stereo camera system. However, many of the algorithms introduced here have a wider impact, particularly in robot hand-eye calibration with all its different areas of application. Stereo self-calibration refers to the computation of the intrinsic and extrinsic parameters of a stereo rig using neither a priori knowledge on the movement of the rig nor on the geometry of the observed scene. The stereo parameters obtained by self-calibration, namely rotation and translation from left to right camera, are used for computing depth maps for both images, which are applied for rendering correctly occluded virtual objects into a real scene (Augmented Reality). The proposed methods were evaluated on real and synthetic data and compared to algorithms from the literature. In addition to a stereo rig, an optical tracking system with a camera mounted on an endoscope was calibrated without a calibration pattern using the proposed extended hand-eye calibration algorithm. The self-calibration methods developed in this work have a number of features, which make them easily applicable in practice: They rely on temporal feature tracking only, as this monocular tracking in a continuous image sequence is much easier than left-to-right tracking when the camera parameters are still unknown. Intrinsic and extrinsic camera parameters are computed during the self-calibration process, i.e., no calibration pattern is required. The proposed stereo self-calibration approach can also be used for extended hand-eye calibration, where the eye poses are obtained by structure-from-motion rather than from a calibration pattern. An inherent problem to hand-eye calibration is that it requires at least two general movements of the cameras in order to compute the rigid transformation. If the motion is not general enough, only a part of the parameters can be obtained, which would not be sufficient for computing depth maps. Therefore, a main part of this work discusses methods for data selection that increase the robustness of hand-eye calibration. Different new approaches are shown, the most successful ones being based on vector quantization. The data selection algorithms developed in this work can not only be used for stereo self-calibration, but also for classic robot hand-eye calibration, and they are independent of the actually used hand-eye calibration algorithm. KW - Augmented Reality (AR) KW - Stereo Self-Calibration Y1 - 2018 PB - Logos CY - Berlin ER - TY - CHAP A1 - Schmidt, Jochen A1 - Wong, C.K. A1 - Yeap, W.K. T1 - Mapping and Localisation with Sparse Range Data T2 - International Conference on Autonomous Robots and Agents (ICARA), pages 497-502, Palmerston North, New Zealand N2 - We present an approach for indoor mapping and localization with a mobile robot using sparse range data, without the need for solving the SLAM problem. The paper consists of two main parts. First, a split and merge based method for dividing a given metric map into distinct regions is presented, thus creating a topological map in a metric framework. Spatial information extracted from this map is then used for self-localization. The robot computes local confidence maps for two simple localization strategies based on distance and relative orientation of regions. The local confidence maps are then fused using an approach adapted from computer vision to produce overall confidence maps. Experiments on data acquired by mobile robots equipped with sonar sensors are presented. KW - Mobile Robots KW - Mapping KW - Localization Y1 - 2018 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Wong, C.K. A1 - Yeap, W.K. T1 - A Split & Merge Approach to Metric-Topological Map-Building T2 - International Conference on Pattern Recognition (ICPR), volume 3, pages 1069-1072, Hong Kong N2 - We present a novel split and merge based method for dividing a given metric map into distinct regions, thus effectively creating a topological map on top of a metric one. The initial metric map is obtained from range data that are converted to a geometric map consisting of linear approximations of the indoor environment. The splitting is done using an objective function that computes the quality of a region, based on criteria such as the average region width (to distinguish big rooms from corridors) and overall direction (which accounts for sharp bends). A regularization term is used in order to avoid the formation of very small regions, which may originate from missing or unreliable sensor data. Experiments based on data acquired by a mobile robot equipped with sonar sensors are presented, which demonstrate the capabilities of the proposed method. KW - Pattern Recognition KW - Metric-Topological Map-Building Y1 - 2018 ER - TY - CHAP A1 - Wong, C.K. A1 - Yeap, W.K. A1 - Schmidt, Jochen T1 - Computing a Network of ASRs Using a Mobile Robot Equipped with Sonar Sensors T2 - International Conference on Robotics, Automation, and Mechatronics (RAM), pages 57-62, Bangkok, Thailand N2 - This paper presents a novel algorithm for computing absolute space representations (ASRs) in Yeap, W.K. and Jefferies, M. (1988) for mobile robots equipped with sonar sensors and an odometer. The robot is allowed to wander freely (i.e. without following any fixed path) along the corridors in an office environment from a given start point to an end point. It then wanders from the end point back to the start point. The resulting ASRs computed in both directions are shown KW - Robotics KW - Automation and Mechatronics Y1 - 2006 ER - TY - CHAP A1 - Yeap, W.K. A1 - Wong, C.K. A1 - Schmidt, Jochen T1 - Initial Experiments with a Mobile Robot on Cognitive Mapping T2 - International Symposium on Practical Cognitive Agents and Robots (PCAR 2006), pages 221-230, Perth, Australia N2 - This paper shows how a mobile robot equipped with sonar sensors and an odometer is used to test ideas about cognitive mapping. The robot first explores an office environment and computes a "cognitive map" which is a network of ASRs [1]. The robot generates two networks, one for the outward journey and the other for the journey home. It is shown that both networks are different. The two networks, however, are not merged to form a single network. Instead, the robot attempts to use distance information implicit in the shape of each ASR to find its way home. At random positions in the homeward journey, the robot calculates its orientation towards home. The robot's performances for both problems are evaluated and found to be surprisingly accurate. KW - Mobile Robot KW - Cognitive Mapping Y1 - 2006 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Vogt, F. A1 - Niemann, H. T1 - Calibration-Free Hand-Eye Calibration: A Structure-from-Motion Approach T2 - Joint Pattern Recognition Symposium N2 - The paper presents an extended hand-eye calibration approach that, in contrast to the standard method, does not require a calibration pattern for determining camera position and orientation. Instead, a structure-from-motion algorithm is applied for obtaining the eye-data that is necessary for computing the unknown hand-eye transformation. Different ways of extending the standard algorithm are presented, which mainly involves the estimation of a scale factor in addition to rotation and translation. The proposed methods are experimentally compared using data obtained from an optical tracking system that determines the pose of an endoscopic camera. The approach is of special interest in our clinical setup, as the usage of an unsterile calibration pattern is difficult in a sterile environment. KW - Translation Vector KW - Feature Tracking KW - World Coordinate System KW - Dual Quaternion Y1 - 2005 PB - Springer CY - Berlin ER - TY - CHAP A1 - Zinßler, T. A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Point Set Registration with Integrated Scale Estimation T2 - Proceedings of the Eighth International Conference on Pattern Recognition and Image Processing (PRIP 2005), pages 116-119, Minsk, Republic of Belarus N2 - Wepresentaniterativeregistrationalgorithmfor aligning two differently scaled 3-D point sets. It extends the popular Iterative Closest Point (ICP) algorithm by estimating a scale factor between the two point sets in every iteration. The presented algorithm is especially useful for the registration of point sets generated by structure-frommotion algorithms, which only reconstruct the 3-D structure of a scene upto scale. LiketheoriginalICPalgorithm,thepresentedalgorithm requires a rough pre-alignment of the point sets. In order to determine the necessary accuracy of the pre-alignment, wehaveexperimentallyevaluatedthebasinofconvergence of the algorithm with respect to the initial rotation, translation, andscale factor between the two point sets. KW - Iterative Closest Point KW - Scale Estimation Y1 - 2005 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Vogt, F. A1 - Niemann, H. T1 - Vector Quantization Based Data Selection for Hand-Eye Calibration T2 - Vision, Modeling, and Visualization 2004, pages 21-28, Stanford, USA N2 - The paper presents a new vectorquantization based Approach for selecting well-suited data for hand-eye calibration from a given sequence of hand and eye movements. Data selection is essential if control of the movements used for calibration is not possible, especially when using continuously recorded data. The new algorithm is compared to another method for data selection as well as to the processing of subsequent movements. Experimental results on real and synthetic data sets show the superior performance of the new approach with respect to calibration errors and computation time. Real data has been obtained from an optical tracking system and a camera mounted on an endoscope, the goal being the reconstruction of medical lightfields. KW - Vector Quantization KW - Hand-Eye Calibration KW - Data selection Y1 - 2005 ER - TY - JOUR A1 - Vogt, F. A1 - Krüger, S. A1 - Schmidt, Jochen A1 - Paulus, D. A1 - Niemann, H. A1 - Hohenberger, W. A1 - C. H., Schick T1 - Light Fields for Minimal Invasive Surgery Using an Endoscope Positioning Robot JF - Methods of Information in Medicine N2 - OBJECTIVES: To generate a fast and robust 3-D visualization of the operation site during minimal invasive surgery. METHODS: Light fields are used to model and visualize the 3-D operation site during minimal invasive surgery. An endoscope positioning robot provides the position and orientation of the endoscope. The a priori un-known transformation from the endoscope plug to the endoscope tip (hand-eye transformation) can either be determined by a three-step algorithm, which includes measuring the endoscope length by hand or by using an automatic hand-eye calibration algorithm. Both methods are described in this paper and their respective computation times and accuracies are compared. RESULTS: Light fields were generated during real operations and in the laboratory. The comparison of the two methods to determine the unknown hand-eye transformation was done in the laboratory. The results which are being presented in this paper are: rendered images from the generated light fields, the calculated extrinsic camera parameters and their accuracies with respect to the applied hand-eye calibration method, and computation times. CONCLUSION: Using an endoscope positioning robot and knowing the hand-eye transformation, the fast and robust generation of light fields for minimal invasive surgery is possible. KW - Robotics Y1 - 2004 ER - TY - CHAP A1 - Schmidt, Jochen A1 - Vogt, F. A1 - Niemann, H. T1 - Robust Hand-Eye Calibration of an Endoscopic Surgery Robot Using Dual Quaternions T2 - Pattern Recognition, Proceedings of the 25th DAGM Symposium, Magdeburg N2 - This paper presents an approach for applying a dual quaternion hand–eye calibration algorithm on an endoscopic surgery robot. Special focus is on robustness, since the error of position and orientation data provided by the robot can be large depending on the movement actually executed. Another inherent problem to all hand–eye calibration methods is that non–parallel rotation axes must be used; otherwise, the calibration will fail. Thus we propose a method for increasing the numerical stability by selecting an optimal set of relative movements from the recorded sequence. Experimental evaluation shows the error in the estimated transformation when using well–suited and ill–suited data. Additionally, we show how a RANSAC approach can be used for eliminating the erroneous robot data from the selected movements. KW - Pattern Recognition KW - Temporal Orderr KW - Numerical Stability KW - Dual Quaternion  KW - Calibration Pattern  Y1 - 2018 ER - TY - CHAP A1 - Zinßer, T. A1 - Schmidt, Jochen A1 - Niemann, H. T1 - A Refined ICP Algorithm for Robust 3-D Correspondence Estimation T2 - Proceedings of the IEEE International Conference on Image Processing, volume 2, pages 695-698, Barcelona, Spain N2 - Robust registration of two 3-D point sets is a common problem in computer vision. The iterative closest point (ICP) algorithm is undoubtedly the most popular algorithm for solving this kind of problem. In this paper, we present the Picky ICP algorithm, which has been created by merging several extensions of the standard ICP algorithm, thus improving its robustness and computation time. Using pure 3-D point sets as input data, we do not consider additional information like point color or neighborhood relations. In addition to the standard ICP algorithm and the Picky ICP algorithm proposed in this paper, a robust algorithm due to Masuda and Yokoya and the RICP algorithm by Trucco et al. are evaluated. We have experimentally determined the basin of convergence, robustness to noise and outliers, and computation time of these four ICP based algorithms KW - Iterative closest point algorithm KW - Iterative algorithms KW - Noise robustnes KW - Computer vision Y1 - 2003 ER - TY - RPRT A1 - Auer, Veronika A1 - Beneken, Gerd A1 - Brummer, Benjamin A1 - Châteauvieux-Hellwig, Camille A1 - Engler, Benjamin A1 - Gilly, Alexander A1 - Hagl, Rainer A1 - Hummel, Felix A1 - Hummel, Sabine A1 - Karlinger, Peter A1 - Knorr, Ludwig A1 - Köster, Heinrich A1 - Kucich, Martin A1 - Mecking, Simon A1 - Rabold, Andreas A1 - Sandor, Viktor A1 - Schalk, Daniel A1 - Schanda, Ulrich A1 - Schemme, Michael A1 - Schiffner, Ivonne A1 - Schmidt, Jochen A1 - Schugmann, Reinhard A1 - Seidlmeier, Heinrich A1 - Sigg, Ferdinand A1 - Stauss, Kilian A1 - Sussmann, Monika A1 - Wellisch, Ulrich A1 - Wenninger, Marc A1 - Wittmann, Josef A1 - Zscheile, Matthias T1 - Jahresbericht 2016, Forschung - Entwicklung - Innovation N2 - Mit dem jährlich erscheinenden Forschungsbericht möchte die Hochschule Rosenheim einen Einblick in ihre vielfältigen Projekte und Aktivitäten der angewandten Forschung und Entwicklung geben. Im Jahresbericht 2016 wird über Vorhaben im Jahr 2016 berichtet. T3 - Schriftenreihen - Forschungsbericht - 5 KW - Forschung Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:861-opus4-12282 ER - TY - RPRT A1 - Ackermann, Timo A1 - Angermeier, Martin A1 - Auer, Veronika A1 - Beneken, Gerd A1 - Bernhardt, Andreas A1 - Botsch, Rafael A1 - Bücker, Dominikus A1 - Hager, Ralf A1 - Hauck-Bauer, Eva A1 - Heigl, Martin A1 - Hirschmüller, Sebastian A1 - Höllmüller, Janett A1 - Karlinger, Peter A1 - Köster, Heinrich A1 - Krause, Harald A1 - Kucich, Martin A1 - Matthias, Kira A1 - Patzl, Victoria A1 - Plönnigs, René A1 - Posch, Georg A1 - Schanda, Ulrich A1 - Scheerer, Josua A1 - Schlecht, Johannes A1 - Schmidt, Jochen A1 - Stichler, Markus A1 - Uhl, Cornelius A1 - Viehhauser, Peter A1 - Weber, Gabriel A1 - Wolf, Christopher A1 - Zagler, Stefan A1 - Zentgraf, Peter T1 - Forschungsbericht 2013 N2 - Mit dem jährlich erscheinenden Forschungsbericht möchte die Hochschule Rosenheim einen Einblick in ihre vielfältigen Projekte und Aktivitäten der angewandten Forschung und Entwicklung geben. Im Forschungsbericht 2013 wird über Vorhaben im Jahr 2013 berichtet. T3 - Schriftenreihen - Forschungsbericht - 2 KW - Forschung Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:861-opus4-12324 ER - TY - JOUR A1 - Wenninger, Marc A1 - Bayerl, Sebastian P. A1 - Schmidt, Jochen A1 - Riedhammer, Korbinian T1 - Timage – A Robust Time Series Classification Pipeline JF - Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series. ICANN 2019. Lecture Notes in Computer Science N2 - Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of research. This paper investigates the use of transfer learning in Deep Neural Networks and a 2D representation of time series known as Recurrence Plots. In order to utilize the research done in the area of image classification, where Deep Neural Networks have achieved very good results, we use a Residual Neural Networks architecture known as ResNet. As preprocessing of time series is a major part of every time series classification pipeline, the method proposed simplifies this step and requires only few parameters. For the first time we propose a method for multi time series classification: Training a single network to classify all datasets in the archive with one network. We are among the first to evaluate the method on the latest 2018 release of the UCR archive, a well established time series classification benchmarking dataset. KW - neural networks Y1 - 2019 VL - 11730 PB - Springer CY - Cham ER - TY - JOUR A1 - Wenninger, Marc A1 - Stecher, Dominik A1 - Schmidt, Jochen T1 - SVM-Based Segmentation of Home Appliance Energy Measurements JF - Proceedings 8th IEEE International Conference on Machine Learning and Applications -ICMLA 2019 N2 - Generating a more detailed understanding of domestic electricity demand is a major topic for energy suppliers and householders in times of climate change. Over the years there have been many studies on consumption feedback systems to inform householders, disaggregation algorithms for Non-Intrusive-Load-Monitoring (NILM), Real-Time-Pricing (RTP) to promote supply aware behavior through monetary incentives and appliance usage prediction algorithms. While these studies are vital steps towards energy awareness, one of the most fundamental challenges has not yet been tackled: Automated detection of start and stop of usage cycles of household appliances. We argue that most research efforts in this area will benefit from a reliable segmentation method to provide accurate usage information. We propose a SVM-based segmentation method for home appliances such as dishwashers and washing machines. The method is evaluated using manually annotated electricity measurements of five different appliances recorded over two years in multiple households. KW - Machine Learning Y1 - 2019 SP - 1666 EP - 1670 ER - TY - BOOK A1 - Schmidt, Jochen T1 - Grundkurs Informatik - Das Übungsbuch: 148 Aufgaben mit Lösungen KW - Grundlagen Übungen Y1 - 2019 SN - 978-3658259440 PB - Springer Vieweg CY - Wiesbaden ET - 1 ER - TY - JOUR A1 - Neumayer, Martin A1 - Stecher, Dominik A1 - Grimm, Sebastian A1 - Maier, Andreas A1 - Bücker, Dominikus A1 - Schmidt, Jochen T1 - Fault and anomaly detection in district heating substations: A survey on methodology and data sets JF - Energy N2 - District heating systems are essential building blocks for affordable, low-carbon heat supply. Early detection and elimination of faults is crucial for the efficiency of these systems and necessary to achieve the low temperatures targeted for 4th generation district heating systems. Especially methods for fault and anomaly detection in district heating substations are currently of high interest, as faults in substations can be repaired quickly and inexpensively, and smart meter data are becoming widely available. In this paper, we review recent scientific publications presenting data-driven approaches for fault and anomaly detection in district heating substations with a focus on methods and data sets. Our review indicates that researchers use a wide variety of methods, mostly focusing on unsupervised anomaly detection rather than fault detection. This is due to a lack of labeled data sets, preventing the use of supervised learning methods and quantitative analysis. Together with the lack of publicly available data sets, this impedes the accurate comparison of individual methods. To overcome this impediment, increase the comparability of different methods and foster competition, future research should focus on establishing publicly available data sets, and industry-relevant metrics as benchmarks. KW - District heating systems KW - Fault/anomaly detection KW - Machine learning Y1 - 2023 U6 - https://doi.org/10.1016/j.energy.2023.127569 VL - 276 SP - 127569 ER - TY - BOOK A1 - Ernst, Hartmut A1 - Schmidt, Jochen A1 - Beneken, Gerd T1 - Grundkurs Informatik: Grundlagen und Konzepte für die erfolgreiche IT-Praxis – Eine umfassende, praxisorientierte Einführung N2 - Das Buch bietet eine umfassende und praxisorientierte Einführung in die wesentlichen Grundlagen und Konzepte der Informatik. Es umfasst den Stoff, der typischerweise in den ersten Semestern eines Informatikstudiums vermittelt wird, vertieft Zusammenhänge, die darüber hinausgehen und macht sie verständlich. Die Themenauswahl orientiert sich an der langfristigen Relevanz für die praktische Anwendung. Praxisnah und aktuell werden die Inhalte für Studierende der Informatik und verwandter Studiengänge sowie für im Beruf stehende Praktiker vermittelt. KW - Grundlagen Informatik Y1 - 2023 SN - 9783658417789 U6 - https://doi.org/10.1007/978-3-658-41779-6 PB - Springer Vieweg CY - Wiesbaden ET - 8 ER - TY - BOOK A1 - Schmidt, Jochen T1 - Grundkurs Informatik – Das Übungsbuch: 163 Aufgaben mit Lösungen N2 - Das Buch richtet sich an Studierende der Informatik oder verwandter Studiengänge und enthält Übungsaufgaben mit Lösungen aus Gebieten, die typischerweise in den ersten Semestern als Grundlagen behandelt werden. Ausgenommen ist der Bereich des Programmierens. Das Buch ergänzt den Grundkurs Informatik mit Übungen zu ausgewählten Kapiteln, ist aber auch in Kombination mit anderen Lehrbüchern verwendbar. KW - Grundlagen Informatik Y1 - 2023 SN - 978-3658434427 U6 - https://doi.org/10.1007/978-3-658-43443-4 PB - Springer Vieweg CY - Wiesbaden ET - 3 ER -