50 citations · 60 across the 9 of their papers we have counts for
5 papers · 1 filter
Object Recognition from very few Training Examples for Enhancing Bicycle Maps
Christoph Reinders, Hanno Ackermann, Michael Ying Yang +1
In recent years, data-driven methods have shown great success for extracting information about the infrastructure in urban areas. These algorithms are usually trained on large data…
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection
Florian Kluger, Hanno Ackermann, Michael Ying Yang +1
We present a novel approach for vanishing point detection from uncalibrated monocular images. In contrast to state-of-the-art, we make no a priori assumptions about the observed sc…
A Kinematic Chain Space for Monocular Motion Capture
Bastian Wandt, Hanno Ackermann, Bodo Rosenhahn
This paper deals with motion capture of kinematic chains (e.g. human skeletons) from monocular image sequences taken by uncalibrated cameras. We present a method based on projectin…
Who With Whom And How?: Extracting Large Social Networks Using Search Engines
Stefan Siersdorfer, Philipp Kemkes, Hanno Ackermann +1
Social network analysis is leveraged in a variety of applications such as identifying influential entities, detecting communities with special interests, and determining the flow o…
Motion Segmentation via Global and Local Sparse Subspace Optimization
Michael Ying Yang, Hanno Ackermann, Weiyao Lin +2
In this paper, we propose a new framework for segmenting feature-based moving objects under affine subspace model. Since the feature trajectories in practice are high-dimensional a…