Video Surveillance for Helpful Purposes

TNT members involved in this project:
Prof. Dr.-Ing. Jörn Ostermann
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Surveillance systems have been widely deployed in public places, for example to maintain order in a train station with stong people stream, to detect potential dangerous object in airport, to recognize a theft in a store, etc. Traditional way in which the surveillance videos are watched by a man sitting before the monitors is unreliable, low efficient and costly. Ideally, we would like the system to automatically analyze the surveillance videos for reporting the speciall situation.


Objects and person of interest are detected by a deep learning-based method, such as Faster RCNN. Each detected object is labeled with an owner. A background model is utilized to find static objects. If the object's ower disappears from the surveillance scene, an alarm for abandonment is triggered. Further events around the abandoned object are analyzed. If anyone attempts to do anything on the under watched object, the person is verified whether he is the owner. If not, a warning for an un-owner moving the object is triggered.  When the person is going to leave the surveillance scene but the missing object is not detected within the scene again, the behavior is recognized as stolen.




In the following sequences, different application of surveillance system are shown.


We provide the Security Event Recognition Dataset (SERD) for research purposes. It is collected and manually labeled by the Institut für Informationsverarbeitung. For more information please contact the authors.  Wentong Liao, M.Sc.


  • E. Nowak, F. Jurie, and B. Triggs, "Sampling strategies for bag-of-features image classification", Proc. ECCV, 2006.
  • David Lowe: "Distinctive Image Features from Scale-Invariant Keypoints", IJCV, 2004.
  • Herbert Bay, Tinne Tuytelaars and Luc Van Gool: "SURF: Speeded Up Robust Features", ECCV, 2006.
  • Krystian Mikolajczyk and Cordelia Schmid: A performance evaluation of local descriptors, TPAMI, 2005.

Show recent publications only
  • Conference Contributions
    • Wentong Liao, Chun Yang, Michael Ying Yang, Bodo Rosenhahn
      Security Event Recognition for Visual Surveillance
      ISPRS Annals of Photogrammetry, Remote Sensing \& Spatial Information Sciences, Vol. 4, June 2017
    • Wentong Liao, Yang Michael, Bodo Rosenhahn
      Video Event Recognition by Combining HDP and Gaussian Process
      IEEE International Conference on Computer Vision (ICCV) Workshop, pp. 19-27, Santiago, Chile, December 2015
    • Wentong Liao, Bodo Rosenhahn, Yang Michael
      Gaussian Process for Activity Modeling and Anomaly Detection
      International Society for Photogrammetry and Remote Sensing ISA workshop, La Grande Motte, France, September 2015
    • Michele Fenzi, Nico Mentzer, Guillermo Payá-Vayá, Tu Ngoc Nguyen, Thomas Risse, Holger Blume, Jörn Ostermann
      Automatic Situation Assessment for Event-driven Video Analysis
      IEEE International Conference on Advanced Video Signal-Based Surveillance (AVSS), accepted as oral presentation , Seoul, South Korea, August 2014
    • Ralf Dragon, Bodo Rosenhahn, Jörn Ostermann
      Multi-Scale Clustering of Frame-to-Frame Correspondences for Motion Segmentation
      12th European Conference on Computer Vision (ECCV 2012), Florence, October 2012
    • Michele Fenzi, Ralf Dragon, Laura Leal-Taixé, Bodo Rosenhahn, Jörn Ostermann
      3D Object Recognition and Pose Estimation for Multiple Objects using Multi-Prioritized RANSAC and Model Updating
      Annual Symposium of the German Association for Pattern Recognition (DAGM), accepted as oral presentation , Graz, Austria, August 2012
    • Ralf Dragon, Muhammad Shoaib, Bodo Rosenhahn, Jörn Ostermann
      NF-Features - No-Feature-Features for Representing non-Textured Regions
      11th European Conference on Computer Vision (ECCV 2010), Heraklion, Greece, September 2010
    • M. Shoaib, T. Elbrandt, R. Dragon, J. Ostermann
      Altcare: Safe Living For Elderly People
      4th International ICST Conference on Pervasive Computing Technologies for Healthcare 2010, IEEE, March 2010
    • M. Shoaib, R. Dragon, J. Ostermann
      Shadow Detection for Moving Humans Using Gradient-Based Background Subtraction
      ICASSP International Conference on Acoustics, Speech and Signal Processing, Taipei, Taiwan, April 2009
    • M. Shoaib, R. Dragon, J. Ostermann
      Improving Object Detection by Contour-Based Shadow Removal
      Zweiter Workshop optische Technologien – HOT, Hannover, November 2008
  • Journals
    • Ralf Dragon, Carsten Dolar, Jörn Ostermann, Matthias Rieger, Holger Blume, Fabian Abel, Philipp Kärger
      Intelligente Videoüberwachung
      UniMagazin, Vol. 3, pp. 34-37, December 2010