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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 -