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H. Ackermann

4 papers hereh-index 14872 citations55 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.SI1

identity via Semantic Scholar / OpenAlex

most citedWho With Whom And How?: Extracting Large Social Networks Using Search Engines

3 citations · 6 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2017★ 1 cited

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…

cs.CV2017

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…

cs.SI2017★ 3 cited

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…

cs.CV2017★ 2 cited

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.