Recognizing events in an automated surveillance system

Orten B., Alatan A. A., Ciloglu T.

MULTIMEDIA CONTENT REPRESENTATION, CLASSIFICATION AND SECURITY, cilt.4105, ss.434-441, 2006 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 4105
  • Basım Tarihi: 2006
  • Dergi Adı: MULTIMEDIA CONTENT REPRESENTATION, CLASSIFICATION AND SECURITY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.434-441
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Event recognition is probably the ultimate purpose of an automated surveillance system. In this paper, hidden Markov models (HMM) are utilized to recognize the nature of an event occurring in a scene. For this purpose, object trajectories, which are obtained through a successful track, are obtained as a sequence of flow vectors that contain instantaneous velocity and location information. These vectors are clustered by K-means algorithm to obtain a prototype representation. HMMs are trained with sequences obtained from usual motion patterns and abnormality is detected by measuring distances to these models. In order to specify the number of models automatically, a novel approach is proposed which utilizes the clues provided by centroid clustering. Preliminary experimental results are promising for detecting abnormal events.