Klaus Debes

View Invariant Appearance-Based Person Reidentification Using Fast Online Feature Selection and Score Level Fusion

Fast and robust person reidentification is an important task in multi-camera surveillance and automated access control. We present an efficient appearance-based algorithm, able to reidentify a person regardless of occlusions, distance to the camera, and changes in view and lighting. The use of fast online feature selection techniques enables us to perform reidentification in hyper-real-time for a multi-camera system, by taking only 10 seconds for evaluating 100 minutes of HD-video data. We demonstrate, that our approach surpasses current appearance-based state-of-the-art in reidentification quality and computational speed and sets a new reference in non-biometric reidentification.

Robot companion for domestic health assistance: Implementation, test and case study under everyday conditions in private apartments

This paper presents the implementation and evaluation results of the German research project SERROGA (2012 till mid 2015), which aimed at developing a robot companion for domestic health assistance for older people that helps keeping them physically and mentally fit to remain living independently in their own homes for as long as possible. The paper gives an overview of the developed companion robot, its system architecture, and essential skills, behaviors, and services required for a robotic health assistant. Moreover, it presents a new approach allowing a quantitative description and assessment of the navigation complexity of apartments to make them objectively comparable for function tests under real-life conditions. Based on this approach, the results of function tests executed in 12 apartments of project staff and seniors are described. Furthermore, the paper presents findings of a case study conducted with nine seniors (aged 68-92) in their own homes, investigating both instrumental and social-emotional functions of a robotic health assistant. The robot accompanied the seniors in their homes for up to three days assisting with tasks of their daily schedule and health care, without any supervising person being present on-site. Results revealed that the seniors appreciated the robots health-related instrumental functions and even built emotional bonds with it.

Mobile Robotic Rehabilitation Assistant for walking and orientation training of Stroke Patients: A report on work in progress

As report on work in progress, this paper describes the objectives and the current state of implementation of the ongoing research project ROREAS (Robotic Rehabilitation Assistant for Stroke Patients), which aims at developing a robotic rehabilitation assistant for walking and orientation exercising in self-training during clinical stroke follow-up care. This requires strongly user-centered, polite and attentive social navigation and interaction behaviors that can motivate the patients to start, continue, and regularly repeat their self-training. Against this background, the paper gives an overview of the constraints and requirements arising from the rehabilitation scenario and the operational environment, a heavily populated multi-level rehabilitation center, and presents the robot platform ROREAS which is currently used for developing the demonstrators (walking coach and orientation coach). Moreover, it gives an overview of the robots functional system architecture and presents selected advanced navigation and HRI functionalities required for a personal robotic trainer that can successfully operate in such a challenging real-world environment, up to the results of ongoing functionality tests and upcoming user studies.

A NEW CONTROL SCHEME FOR COMBUSTION PROCESSES USING REINFORCEMENT LEARNING BASED ON NEURAL NETWORKS

We present a new control scheme for an industrial hard-coal combustion process in a power plant based on reinforcement-learning in combination with neural networks. To comply with the great requirements for environmental protection, the plant operator is interested in a minimization of the nitrogen oxides emission and a maximization of the efficiency factor, while other process parameters have to be kept within predefined limits. To cope with both the tremendous action and state space of the power plant, we present a multiagent-reinforcement-system consisting of 4 agents, which are realized by relatively simple neural function approximators. We demonstrate that our multiagent-system was able to significantly reduce the overall air consumption of the real combustion process of the power plant.

ROREAS: robot coach for walking and orientation training in clinical post-stroke rehabilitation--prototype implementation and evaluation in field trials

This paper describes the objectives and the state of implementation of the ROREAS project which aims at developing a socially assistive robot coach for walking and orientation training of stroke patients in the clinical rehabilitation. The robot coach is to autonomously accompany the patients during their exercises practicing their mobility skills. This requires strongly user-centered, polite and attentive social navigation and interaction abilities that can motivate the patients to start, continue, and regularly repeat their self-training. The paper gives an overview of the training scenario and describes the constraints and requirements arising from the scenario and the operational environment. Moreover, it presents the mobile robot ROREAS and gives an overview of the robot’s system architecture and the required human- and situation-aware navigation and interaction skills. Finally, it describes our three-stage approach in conducting function and user tests in the clinical environment: pre-tests with technical staff, followed by function tests with clinical staff and user trials with volunteers from the group of stroke patients, and presents the results of these tests conducted so far.

Interactive mobile robots guiding visitors in a university building

This paper presents an architectural overview of a robot-based visitor information system in a university building. Two mobile robots serve as mobile information terminals providing information about the employees, labs, meeting rooms, and offices in the building and are able to guide the visitors to these points of interest. The paper focuses on the different software components needed to meet the requirements of the multi-story office building. Furthermore, the integration of a multi-hypotheses person tracker is outlined, which helps the robots to interact with the people in their near surrounding. Besides first observations on interaction, the further development is outlined as well.

Vision-based hyper-real-time object tracker for robotic applications

Fast vision-based object and person tracking is important for various applications in mobile robotics and Human-Robot Interaction. While current state-of-the-art methods use descriptive features for visual tracking, we propose a novel approach using a sparse template based feature set, which is drawn from homogeneous regions on the object to be tracked. Using only a small number of simple features, without complex descriptors in combination with logarithmic-search, the tracker performs at hyper-real-time on HD-images without the use of parallelized hardware. Detailed benchmark experiments show that it outperforms most other state-of-the-art approaches for real-time object and person tracking in quality and runtime. In the experiments we also show the robustness of the tracker and evaluate the effects of different initialization methods, feature sets, and parameters on the tracker. Although we focus on the scenario of person and object tracking in robot applications, the proposed tracker can be used for a variety of other tracking tasks.

APFel: The intelligent video analysis and surveillance system for assisting human operators

The rising need for security in the last years has led to an increased use of surveillance cameras in both public and private areas. The increasing amount of footage makes it necessary to assist human operators with automated systems to monitor and analyze the video data in reasonable time. In this paper we summarize our work of the past three years in the field of intelligent and automated surveillance. Our proposed system extends the common active monitoring of camera footage into an intelligent automated investigative person-search and walk path reconstruction of a selected person within hours of image data. Our system is evaluated and tested under life-like conditions in real-world surveillance scenarios. Our experiments show that with our system an operator can reconstruct a case in a fraction of time, compared to manually searching the recorded data.

Automatic calibration of a stationary network of laser range finders by matching movement trajectories

Laser based detection and tracking of persons can be used for numerous tasks. While a single laser range finder (LRF) is sufficient for detecting and tracking persons on a mobile robot platform, a network of multiple LRF is required to observe persons in larger spaces. Calibrating multiple LRF into a global coordinate system is usually done by hand in a time consuming procedure. An automatic calibration mechanism for such a sensor network is introduced in this paper. Without the need of prior knowledge about the environment, this mechanism is able to obtain the positions and orientations of all LRF in a global coordinate system. By comparing person tracks, determined for each individual LRF unit and matching them, constrains between the LRF units can be calculated. We are able to estimate the poses of all LRF by resolving these constrains. We evaluate and compare our method to the current state of the art approach methodically and experimentally. Experiments show that our calibration approach outperforms this approach.

Konrad and Suse, Two Robots Guiding Visitors in a University Building

This paper presents an overview of the hard- and software architecture of a mobile visitor information system for the Konrad Zuse building of the School of Computer Science and Automation at the Ilmenau University of Technology. Two mobile robots serve as mobile information terminals with capabilities for generating way descriptions and guiding the visitor to the points of interest (labs, meeting rooms, offices, employees) in the building. The paper focuses on the constraints resulting from the challenging environment in this multi-floor building, as well as on the integration aspects of various skills for navigation and human–robot interaction. Besides first experience with the system, the further development is outlined as well.