Now showing items 1-6 of 6

    • Flexible test-bed for unusual behavior detection 

      Petrás I.; Beleznai, C.; Dedeolğu, Yiğithan; Pards, M.; Kovács L.; Szlávik, Z.; Havasi L.; Szirányi, T.; Töreyin, B. Uğur; Güdükbay, Uğur; Çetin, A.hmet Enis; Canton-Ferrer, C. (ACM, 2007-07)
      Visual surveillance and activity analysis is an active research field of computer vision. As a result, there are several different algorithms produced for this purpose. To obtain more robust systems it is desirable to ...
    • Framework for online superimposed event detection by sequential Monte Carlo methods 

      Urfalıoğlu, Onay; Kuruoğlu, E. E.; Çetin, A. Enis (IEEE, 2008-03-04)
      In this paper, we consider online seperation and detection of superimposed events by applying particle filtering. We concentrate on a model where a background process, represented by a 1D-signal, is superimposed by an ...
    • Metadata extraction from text in soccer domain 

      Göktürk, Z. O.; Çiçekli, N. K.; Çiçekli, İlyas (IEEE, 2008-10)
      Event detection is a crucial part for soccer video searching and querying. The event detection could be done by video content itself or from a structured or semi structured text files gathered from sports web sites. In ...
    • New event detection and topic tracking in Turkish 

      Can, F.; Kocberber, S.; Baglioglu, O.; Kardas, S.; Ocalan, H. C.; Uyar, E. (John Wiley & Sons, Inc., 2010)
      Topic detection and tracking (TDT) applications aim to organize the temporally ordered stories of a news stream according to the events. Two major problems in TDT are new event detection (NED) and topic tracking (TT). These ...
    • On-line new event detection and tracking in a multi-resource environment 

      Kurt, Hakan (Bilkent University, 2001)
      As the amount of electronically available information resources increase, the need for information also increases. Today, it is almost impossible for a person to keep track all the information resources and find new ...
    • Superimposed event detection by sequential Monte Carlo methods 

      Urfalıoğlu, O.; Kuruoğlu, E. E.; Çetin, Ahmet Enis (IEEE, 2007)
      In this paper, we consider the detection of rare events by applying particle filtering. We model the rare event as an AR signal superposed on a background signal. The activation and deactivation times of the AR-signal are ...