Video Surveillance for Helpful Purposes

TNT members involved in this project:
Wentong Liao, M.Sc.
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Nowadays surveillance systems are installed to fight criminals. Locations with high surveillance camera densities make people feel unsafe. The initial idea of this project is to use information from surveillance cameras to objectively enhance security by detecting all-day accidents thus helping non-criminals. The project is situated inside the Forschungsinitiative Sicherheit (see university and project website) where interdisciplinary research around the topic security and safety is performed.

Object shapes are extracted in front of a static background which is learned and updated. In the next step, the object appearance is modeled using an object-wise bag-of-features-approach (BoF) in combination with different types of keypoint descriptors like SIFT, SURF or GLOH.

The BoF-Approach allows to identify individual objects even in merge-situations with partial occlusions. Besides, generalizations for the purpose of classifications are easy to train when the BoF is generalization-wide e.g., a "human people BoF".

As an application of the estimated methods, the BMBF-funded project ASEV has been launched.


In the following sequences, object tracking is performed only with the usage of keypoint features. So the object position which is not suitable in many tracking situations was not used.


  • 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 all publications
  • 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
  • Wentong Liao, Yang Michael, Bodo Rosenhahn
    Video Event Recognition by Combining HDP and Gaussian Process
    IEEE International Conference on Computer Vision (ICCV) Workshops, pp. 19-27, Santiago, Chile, 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