T
Timm Linder
Researcher at Bosch
Publications - 29
Citations - 813
Timm Linder is an academic researcher from Bosch. The author has contributed to research in topics: Context (language use) & Pose. The author has an hindex of 11, co-authored 27 publications receiving 612 citations. Previous affiliations of Timm Linder include RWTH Aachen University & University of Duisburg-Essen.
Papers
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Book ChapterDOI
SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports
Rudolph Triebel,Kai O. Arras,Rachid Alami,Lucas Beyer,Stefan Breuers,Raja Chatila,Mohamed Chetouani,Daniel Cremers,Vanessa Evers,Michelangelo Fiore,Hayley Hung,Omar Adair Islas Ramirez,Michiel Joosse,Harmish Khambhaita,Tomasz Piotr Kucner,Bastian Leibe,Achim J. Lilienthal,Timm Linder,Manja Lohse,Martin Magnusson,Billy Okal,Luigi Palmieri,Umer Rafi,Marieke M. J. W. van Rooij,Lu Zhang,Lu Zhang +25 more
TL;DR: How the SPENCER project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors is described.
Proceedings ArticleDOI
On multi-modal people tracking from mobile platforms in very crowded and dynamic environments
TL;DR: A fully integrated real-time multi-modal laser/RGB-D people tracking framework for moving platforms in environments like a busy airport terminal is proposed, which indicates that more complex data association methods may not always be the better choice, and derive possible future research directions.
Journal ArticleDOI
Hybreed: A software framework for developing context-aware hybrid recommender systems
TL;DR: Hybreed is the first framework to cover aspects known from context processing frameworks with features of state-of-the-art recommender system frameworks, aspects that have been addressed only separately in previous research.
Posted Content
How Robust is 3D Human Pose Estimation to Occlusion
TL;DR: This work takes a first step in improving occlusion-robustness through training data augmentation with synthetic occlusions and turns out to be an effective regularizer that is beneficial even for non-occluded test cases.
Journal ArticleDOI
MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation
TL;DR: This work proposes metric-scale truncation-robust volumetric heatmaps, whose dimensions are all defined in metric 3D space, instead of being aligned with image space, and finds that supervision via absolute pose loss is crucial for accurate non-root-relative localization.