Guldogan, M. B.
Gustafsson, F.
Orguner, Umut
Bjorklund, S.
Petersson, H.
Nezirovic, A.
Monitoring and tracking human activities around restricted areas is an important issue in security and surveillance applications. The movement of different parts of the human body generates unique micro-Doppler features which can be extracted effectively using joint time-frequency analysis. In this paper, we describe the simultaneous tracking of both location and micro-Doppler features of a human using particle filters (PF). The results obtained using the data from a 77 GHz radar prove the successful usage of particle filters in tracking micro-Doppler features of the human gait.


Automated crowd behavior analysis for video surveillance applications
Güler, Püren; Temizel, Alptekin; Taşkaya Temizel, Tuğba; Department of Information Systems (2012)
Automated analysis of a crowd behavior using surveillance videos is an important issue for public security, as it allows detection of dangerous crowds and where they are headed. Computer vision based crowd analysis algorithms can be divided into three groups; people counting, people tracking and crowd behavior analysis. In this thesis, the behavior understanding will be used for crowd behavior analysis. In the literature, there are two types of approaches for behavior understanding problem: analyzing behavi...
Radar micro-doppler parameter estimation of human motion using particle filters Parcacik suzgeci̇ kullanilarak i̇nsan yürüyüş ü radar mi̇kro-doppler parametreleri̇ni̇n kesti̇ rilmesi̇
Guldogan, M.B.; Gustafsson, F.; Orguner, Umut; Björklund, S.; Petersson, H.; Nezirovic, A. (2011-04-22)
Guvenlikli b ¨ olgeler c¸evresinde olabilecek insan hareketlerinin tespit ¨ edilip izlenmesi guvenlik ve g ¨ ozetleme uygulamalarının c ¨ ¸ok onemli ¨ bir parc¸asını olus¸turur. ˙Insan vucudu hareket halinde iken, ¨ radar sinyallerinin vucudun de ¨ gis¸ik kısımlarından yansıması sonucu ˘ zaman-frekans duzleminde karakteristik mikro-Doppler ¨ oznitelikleri ¨ olus¸ur. Bu oznitelikler, birles¸ik zaman-frekans analizleri kul- ¨ lanılarak etkili bir s¸ekilde sec¸ilip c¸ıkarılabilinir. Bu makalede, insan hedefin ...
Object tracking for surveillance applications using thermal and visible band video data fusion
Beyan, Çiğdem; Temizel, Alptekin; Department of Information Systems (2010)
Individual tracking of objects in the video such as people and the luggages they carry is important for surveillance applications as it would enable deduction of higher level information and timely detection of potential threats. However, this is a challenging problem and many studies in the literature track people and the belongings as a single object. In this thesis, we propose using thermal band video data in addition to the visible band video data for tracking people and their belongings separately for ...
Collaborative mobile target imaging in ultra-wideband wireless radar sensor networks
Arık, Muharrem; Akan, Özgür Barış; Department of Electrical and Electronics Engineering (2008)
Wireless sensor networks (WSN) have thus far been used for detection and tracking of static and mobile targets for surveillance and security applications. However, detection and tracking do not suffice for a complete satisfaction of these applications and an accurate target classification. To address this need, among various target classification methods, imaging of target yields the most valuable information. Nevertheless, imaging of mobile targets moving over an area requires networked and collaborative d...
Particle filter based Conjoint Individual-Group Tracker (CIGT)
YİĞİT, Ahmet; Temizel, Alptekin (2015-08-28)
In this paper, we present a method for joint tracking of individuals and groups in surveillance scenarios. Groups are dynamic entities and they may grow or shrink with merge-split events. This dynamic nature makes it difficult to track groups using conventional trackers. In this paper, we propose a new tracking method named Conjoint Individual and Group Tracker (CIGT) based on particle filter with multi-observation model and particle advection. The proposed multi-observation model uses in-group and out-grou...
Citation Formats
M. B. Guldogan, F. Gustafsson, U. Orguner, S. Bjorklund, H. Petersson, and A. Nezirovic, “HUMAN GAIT PARAMETER ESTIMATION BASED ON MICRO-DOPPLER SIGNATURES USING PARTICLE FILTERS,” 2011, Accessed: 00, 2020. [Online]. Available: