Timm Linder

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.

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.

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.

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.

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.