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J. Intell. Syst. Appl.
E-ISSN: 2667-6893
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Anomaly Detection with Structural Similarity and Optical Flow Histogram

Yapısal Benzerlik ve Optik Akış Histogramı ile Anomali Tespiti

How to cite: Öz K, Karaş R. Anomaly detection with structural similarity and optical flow histogram. Akıllı Sistemler ve Uygulamaları Dergisi (Journal of Intelligent Systems with Applications) 2018; 1(2): 127-130. DOI: 10.54856/jiswa.201812040

Full Text: PDF, in Turkish.

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Title: Anomaly Detection with Structural Similarity and Optical Flow Histogram

Abstract: In this paper, we present an anomaly detection and localization system for surveillance systems. A new feature descriptor is proposed. The spatio-temporal identifiers are obtained by using optical flow histogram and the structural similarity index from the videos that contain normal conditions. An artificial neural network, Selforganizing maps are used in modeling. The proposed system has been tested on the UCSD dataset.

Keywords: Anomaly detection; optical flow histogram; structural similarity index; video surveillance

Başlık: Yapısal Benzerlik ve Optik Akış Histogramı ile Anomali Tespiti

Özet: Bu çalışmada, gözetim sistemleri için tasarlanmış bir anomali tespit ve lokalizasyon sistemi sunulmaktadır. Yeni bir özellik tanımlayıcı önerilmektedir. Normal durumları içeren videolardan optik akış histogramı ve yapısal benzerlik indeksi kullanılarak konum-zamansal tanımlayıcılar elde edilmektedir. Modellemede yapay sinir ağlarından öz düzenleyici haritalar kullanılmaktadır. Önerilen sistem UCSD verisetinde denenmiştir.

Anahtar kelimeler: Anomali tespiti; optik akış histogramı; yapısal benzerlik indisi; video gözetim

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