ROREAS: robot coach for walking and orientation training in clinical post-stroke rehabilitation - prototype implementation and evaluation in field trials. - In: Autonomous robots, ISSN 1573-7527, Bd. 41 (2017), 3, S. 679-698
http://dx.doi.org/10.1007/s10514-016-9552-6
Are color features important for person detection? - insights into features learned by deep convolutional neural networks. - In: 22. Workshop Farbbildverarbeitung, (2016), S. 169-182
Contribution towards evaluating the practicability of socially assistive robots - by example of a mobile walking coach robot. - In: Social Robotics, (2016), S. 890-899
http://dx.doi.org/10.1007/978-3-319-47437-3_87
Cooperative multi-scale Convolutional Neural Networks for person detection. - In: 2016 International Joint Conference on Neural Networks (IJCNN), ISBN 978-1-5090-0620-5, (2016), S. 267-276
http://dx.doi.org/10.1109/IJCNN.2016.7727208
Assistive robotics for health assistance - a contribution towards evaluating the practicability by example of a mobile rehab robot :
Assistenzrobotik für die Gesundheitsassistenz - ein Beitrag zur Evaluierung der Praxistauglichkeit am Beispiel eines mobilen Reha-Roboters. - In: Zukunft Lebensräume, ISBN 978-3-8007-4212-7, (2016), S. 58-67
May I be your personal coach? : bringing together person tracking and visual re-identification on a mobile robot. - In: Robotics in the era of digitalisation, (2016), S. 141-148
User recognition for guiding and following people with a mobile robot in a clinical environment. - In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), (2015), S. 3600-3607
Rehabilitative follow-up care is important for stroke patients to regain their motor and cognitive skills. We aim to develop a robotic rehabilitation assistant for walking exercises in late stages of rehabilitation. The robotic rehab assistant is to accompany inpatients during their self-training, practicing both mobility and spatial orientation skills. To hold contact to the patient, even after temporally full occlusions, robust user re-identification is essential. Therefore, we implemented a person re-identification module that continuously re-identifies the patient, using only few amount of the robot's processing resources. It is robust to varying illumination and occlusions. State-of-the-art performance is confirmed on a standard benchmark dataset, as well as on a recorded scenario-specific dataset. Additionally, the benefit of using a visual re-identification component is verified by live-tests with the robot in a stroke rehab clinic.
http://dx.doi.org/10.1109/IROS.2015.7353880
Evaluation of multi feature fusion at score-level for appearance-based person re-identification. - In: International Joint Conference on Neural Networks (IJCNN), 2015, ISBN 978-1-4799-1961-1, (2015), insges. 8 S.
Robust appearance-based person re-identification can only be achieved by combining multiple diverse features describing the subject. Since individual features perform different, it is not trivial to combine them. Often this problem is bypassed by concatenating all feature vectors and learning a distance metric for the combined feature vector. However, to perform well, metric learning approaches need many training samples which are not available in most real-world applications. In contrast, in our approach we perform score-level fusion to combine the matching scores of different features. To evaluate which score-level fusion techniques perform best for appearance-based person re-identification, we examine several score normalization and feature weighting approaches employing the the widely used and very challenging VIPeR dataset. Experiments show that in fusing a large ensemble of features, the proposed score-level fusion approach outperforms linear metric learning approaches which fuse at feature-level. Furthermore, a combination of linear metric learning and score-level fusion even outperforms the currently best non-linear kernel-based metric learning approaches, regarding both accuracy and computation time.
http://dx.doi.org/10.1109/IJCNN.2015.7280360
Robotischer Reha-Assistent zum Lauftraining von Patienten nach Schlaganfall: erste Ergebnisse zum Laufcoach. - In: 8. AAL-Kongress, (2015), S. 436-445
In diesem Beitrag werden erste Ergebnisse zum Einsatz eines robotischen Reha-Assistenten als Laufcoach in einer Klinik vorgestellt. Zunächst wird das mit Laufcoach bezeichnete Einsatzszenario beschrieben und die zur Umsetzung dieses Szenarios grundlegenden Roboterverhalten sowie die eingesetzten realwelttauglichen Erkennungs-, Navigations- und Interaktionsleistungen zusammen mit der Roboterplattform vorgestellt. Die Herangehensweise an zunächst 4-tägige Funktionstests in der Klinik mit 15.000 m gefahrener Wegstrecke wird dargelegt und erste erreichte Ergebnisse zu den Roboterverhalten der autonomen und höflichen Zielanfahrt, des Lotsens und Folgens einer Person diskutiert.
Analyse von Personenbewegungen an Flughäfen mittels zeitlich rückwärts- und vorwärtsgerichteter Videodatenströme (APFel), Teilvorhaben: Video- und Laser basiertes Personentracking und Trajektorienanalyse (VILPERT) : Schlussbericht ; Berichtszeitraum: 01.01.2010 - 31.03.2014. - Ilmenau. - Online-Ressource (PDF-Datei: 38 S., 3.520 KB)Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden
https://edocs.tib.eu/files/e01fb15/83516070X.pdf