Eric Müller-Budack (M.Eng.)

In my research, I address visual information extraction from images and videos. More specifically, I deal with object segmentation and classification, acquisition date and geolocation estimation, face recognition, and 3-D monocular depth calculation from individual 2-D images. In this context, I focus on investigating machine learning and deep learning methods.

• E. Müller-Budack, J. Theiner, S. Diering, M. Idahl, R. Ewerth:
  Multimodal Analytics for Real-world News using Measures of Cross-modal Entity Consistency
  In: ACM International Conference on Multimedia Retrieval (ICMR), Dublin, Ireland, 2020, accepted for publication (full paper)

• D. Morris, E. Müller-Budack, R. Ewerth:
  SlideImages: A Dataset for Educational Image Classification
  In: European Conference on Information Retrieval (ECIR), Lisboa, Portugal, 2020, 289-296.  https://doi.org/10.1007/978-3-030-45442-5_36

  https://arxiv.org/pdf/2001.06823.pdf 

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• E. Müller-Budack, J. Theiner, R. Rein, R. Ewerth:
  "Does 4-4-2 exist?" -: An Analytics Approach to Understand and Classify Football Team Formations in Single Match Situations
  In: Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports @ACM MM, Nice, France, 2019, 25-33.

  https://arxiv.org/pdf/1910.00412

• E. Müller-Budack, K. Pustu-Iren, R. Ewerth:
  Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification
  In: Proceedings of European Conference on Computer Vision (ECCV), München, 2018, 575-592.

  http://openaccess.thecvf.com/content_ECCV_2018/html/Eric_Muller-Budack_Geolocation_Estimation_of_ECCV_2018_paper.html

• E. Müller-Budack, K. Pustu-Iren, S. Diering, R. Ewerth:
  Finding Person Relations in Image Data of News Collections in the Internet Archive
  In Proceedings of International Conference on Theory and Practice of Digital Libraries (TPDL), Porto, Portugal, 2018, 229-240. “Honorable Mention Award”

  https://arxiv.org/abs/1806.08246

• M. Mühling, N. Korfhage, E. Müller, C. Otto, M. Springstein, T. Langelage, U. Veith, R. Ewerth, B. Freisleben: 
  Deep learning for content-based video retrieval in film and television production. 
  In Multimedia Tools and Applications, 2017, 1-26. 
  https://link.springer.com/article/10.1007/s11042-017-4962-9
   
• R. Ewerth, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok, K. Dembczyński, E. Hüllermeier:
  Estimating Relative Depth in Single Images via Rankboost
  In: Proceedings of IEEE 18th International Conference on Multimedia & Expo (ICME), Hongkong, IEEE Press, 2017, 919-924.
  https://doi.org/10.1109/ICME.2017.8019434
   
• E. Müller, M. Springstein, R. Ewerth: 
  "When was this picture taken?" – Image Date Estimation in the Wild
  In: Proceedings of 39th European Conference on Information Retrieval (ECIR), Aberdeen, UK, 2017, 619-625.
  https://link.springer.com/chapter/10.1007/978-3-319-56608-5_57
   
• E. Müller, C. Otto, R. Ewerth: 
  Semi-supervised Identification of Rarely Appearing Persons in Video by Correcting Weak Labels
  In: Proceedings of ACM International Conference on Multimedia Retrieval (ICMR), New York, ACM, 2016, 381-384
  http://dl.acm.org/citation.cfm?id=2912073
   
• A. Breitbarth, E. Müller, P. Kühmstedt, G. Notni, J. Denzler: 
  Phase unwrapping of fringe images for dynamic 3D measurements without additional pattern projection 
  In: SPIE Sensing Technology + Applications. International Society for Optics and Photonics, 2015, 948903-948903-10