• In general: computer vision algorithms, image and video processing, machine learning ("old school" as well as deep learning)
• More specifically: human pose estimation with a focus on human pose analysis, kinematic and dynamic parameter prediction from pose estimates in video footage

• Swimmer detection and pose estimation for continuous stroke rate determination
• Deep Ski-Jump Pose

Dan Zecha. Motion Kinematics and Dynamics Prediction Using Human Pose Estimation in Videos: Towards Automated Kinematical Profiling of Swimmers and Ski Jumpers.
Dissertation, University of Augsburg, July. 10, 2019. ( Official) [ PDF]

• Moritz Einfalt, Charles Dampeyrou, Dan Zecha, Rainer Lienhart.
  Frame-level Event Detection in Athletics Videos with Pose-based Convolutional Sequence Networks.
  Second International ACM Workshop on Multimodal Content Analysis in Sports (ACM MMSports'19), part of ACM Multimedia 2019. Nice, France, October 2019. [ ACM-DL PDF]

• Dan Zecha, Moritz Einfalt, Rainer Lienhart. 
  Refining Joint Locations for Human Pose Tracking in Sports Videos. 
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2019. Long Beach, CA, USA, June 2019. [ CVF PDF]

• Philipp Harzig, Dan Zecha, Rainer Lienhart, Carolin Kaiser, René Schallner. 
  Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for Marketing.
  IEEE MIPR 2019. San José, CA, USA, March 2019. [ PDF]

• Rainer Lienhart, Moritz Einfalt, Dan Zecha.
  Mining Automatically Estimated Poses from Video Recordings of Top Athletes.
  IJCSS, December 2018. [ PDF]
• Dan Zecha, Christian Eggert, Moritz Einfalt, Stephan Brehm, Rainer Lienhart.
  A Convolutional Sequence to Sequence Model for Multimodal Dynamics Prediction in Ski Jumps.
  First International ACM Workshop on Multimodal Content Analysis in Sports (ACM MMSports'18), part of ACM Multimedia 2018. Seoul, Korea, October 2018. [ PDF]
• Dan Zecha, Moritz Einfalt, Christian Eggert, Rainer Lienhart.
  Kinematic Pose Rectification for Performance Analysis and Retrieval in Sports.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2018. Salt Lake City, USA, June 2018. [ PDF]
• Moritz Einfalt, Dan Zecha, Rainer Lienhart.
  Activity-conditioned continuous human pose estimation for performance analysis of athletes using the example of swimming.
  IEEE Winter Conference on Applications of Computer Vision 2018 (WACV18), Lake Tahoe, NV, USA, March 2018. [ arXiv IEEE PDF]

• Christian Eggert, Stephan Brehm, Anton Winschel, Dan Zecha, Rainer Lienhart. 
  A Closer Look: Small Object Detection in Faster R-CNN.
  IEEE International Conference on Multimedia and Expo 2017 (ICME 2017). Hong Kong, China, July 2017. [ PDF ]

• Christian Eggert, Stephan Brehm, Dan Zecha, Rainer Lienhart.
  Improving Small Object Proposals for Company Logo Detection.
  ACM International Conference on Multimedia Retrieval 2017 (ICMR 2017). Bucharest, Romania, June 2017. [ arXiv] [ PDF]

• Dan Zecha, Christian Eggert, Rainer Lienhart.
  Pose Estimation for Deriving Kinematic Parameters of Competitive Swimmers.
  Computer Vision Applications in Sports, part of IS&T Electronic Imaging 2017. Burlingame, California, January 2017. [ PD ]

• Christian Eggert, Anton Winschel, Dan Zecha, Rainer Lienhart.
  Saliency-guided Selective Magnification for Company Logo Detection.
  International Conference on Pattern Recognition 2016 (ICPR 2016), Cancun, December 2016.

• Dan Zecha and Rainer Lienhart. 
  Key-Pose Prediction in Cyclic Human Motion.
  IEEE Winter Conference on Applications of Computer Vision 2015 (WACV 2015). Waikoloa Beach, HI, January 6-9, 2015 [ PDF ]

• Dan Zecha, Thomas Greif, and Rainer Lienhart. 
  Swimmer Detection and Pose Estimation for Continuous Stroke Rate Determination. 
  Multimedia Content Access: Algorithms and Systems VI, part of IS&T/SPIE Electronic Imaging, 23 January 2012, Burlingame, California, USA.
  Also Technical Report 2011-13, University of Augsburg, Institute of Computer Science, July 2011. [ PDF] [ Video ]

• Dan Zecha, Jürgen Küchler, Rainer Lienhart. Leistungsdiagnose von Freiwasser- und Beckenschwimmern im Strömungskanal mittels hoch-moderner tiefer neuronaler Netze, 6. BISp Symposium, 13-14 March 2017, SportCentrum Kamen-Kaisenau, Germany.
• Dan Zecha and Rainer Lienhart. Bestimmung intrazyklischer Phasengeschwindigkeiten von Schwimmern im Schwimmkanal mittels vollautomatischer Videoanalyse. DVS Schulung, 27. September 2014, Leipzig, Germany.
• Dan Zecha and Rainer Lienhart. Bestimmung intrazyklischer Phasengeschwindigkeiten von Schwimmern im Schwimmkanal mittels vollautomatischer Videoanalyse. 16 Frühjahrsschule Informations- und Kommunikationstechnologien in der angewandten Trainingswissenschaft, 9-10 April 2014, Leipzig, Germany.
• Dan Zecha and Rainer Lienhart. Automating quantitative performance analyses of swimmers by means of continuous pose estimation in videos. 21 dvs-Hochschultag, 25-27 September 2013, Konstanz, Germany.

• Dan Zecha and Rainer Lienhart. 
  Bestimmung intrazyklischer Phasengeschwindigkeiten von Schwimmern im Schwimmkanal mittels vollautomatischer Videoanalyse. 
  Technical Report 2014-04, University of Augsburg, Institute of Computer Science, July 2014. [ PDF ]

• Dan Zecha. An Analysis and Efficient Implementation of Felzenszwalb's Object Detection System.
  Master Thesis, March 2013. [ PDF ]

• Dan Zecha. Detecting Swimmers and Estimating their Pose in a Swimming Channel.

  Bachelor Thesis, June 2011. [ PDF ]

• SS 2019: Machine Learning & Computer Vision
• SS 2019: Seminar: Multimedia und Maschinelles Sehen
• WS 2018: Probabilistic Robotics
• WS 2018: Seminar: Multimediale Datenverarbeitung
• SS 2018: Machine Learning & Computer Vision
• SS 2018: Seminar: Multimedia und Maschinelles Sehen
• WS 2017: Multimedia Grundlagen I (wechselnde Dozenten)
• WS 2017: Seminar: Multimediale Datenverarbeitung
• SS 2017: Multimedia II: Machine Learning & Computer Vision
• SS 2017: Seminar: Multimedia und Maschinelles Sehen
• WS 2016: Multimedia Grundlagen I
• SS 2016: Multimedia II: Machine Learning & Computer Vision
• SS 2016: Seminar: Multimedia und Maschinelles Sehen
• WS 2015: Multimedia Grundlagen I
• WS 2015: Probabilistic Robotics
• SS 2015: Multimedia II: Machine Learning & Computer Vision
• SS 2015: Seminar: Multimedia und Maschinelles Sehen
• WS 2014: Probabilistic Robotics
• SS 2014: Seminar: Multimedia und Maschinelles Sehen (wechselnde Dozenten)
• SS 2013: Multimedia II: Machine Learning & Computer Vision