Pedestrian zone anomaly detection by non-parametric temporal modelling

With the increasing focus on safety and security in public areas, anomaly detection in video surveillance systems has become increasingly more important. In this paper, we describe a method that models the temporal behavior and detects behavioral anomalies in the scene using probabilistic graphical models. The Coupled Hidden Markov Model (CHMM) method that we use shows that sparse features obtained via feature detection and description algorithms are suitable for modeling the temporal behavior patterns and performing global anomaly detection. We model the scene using these features, perform perspective independent velocity analysis for anomaly detection purposes and demonstrate the results obtained on UCSD pedestrian walkway dataset. The training is unsupervised and does not require any data having anomaly. This eliminates the need to obtain anomaly data and to define anomalies in advance.


Local Anomaly Detection in Crowded Scenes Using Finite-Time Lyapunov Exponent Based Clustering
Öngün, Cihan; Temizel, Alptekin; Taşkaya Temizel, Tuğba (2014-08-29)
Surveillance of crowded public spaces and detection of anomalies from the video is important for public safety and security. While anomaly detection is possible by detection and tracking of individuals in low-density areas, such methods are not reliable in high-density crowded scenes. In this work we propose a holistic unsupervised approach to cluster different behaviors in high density crowds and detect the local anomalies using these clusters. Finite-Time Lyapunov Exponents (FTLE) is used for analyzing th...
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...
Object tracking system with seamless object handover between stationary and moving camera modes
Emeksiz, Deniz; Temizel, Alptekin; Department of Information Systems (2012)
As the number of surveillance cameras and mobile platforms with cameras increases, automated detection and tracking of objects on these systems gain importance. There are various tracking methods designed for stationary or moving cameras. For stationary cameras, correspondence based tracking methods along with background subtraction have various advantages such as enabling detection of object entry and exit in a scene. They also provide robust tracking when the camera is static. However, they fail when the ...
Anomaly detection using sparse features and spatio-temporal hidden markov model for pedestrian zone video surveillance
Gündüz, Ayşe Elvan; Taşkaya Temizel, Tuğba; Temizel, Alptekin; Department of Information Systems (2014)
Automated analysis of crowd behavior for anomaly detection has become an important issue to ensure the safety and security of the public spaces. Public spaces have varying people density and as such, algorithms are required to work robustly in low to high density crowds. Mainly, there are two different approaches for analyzing the crowd behavior: methods based on object tracking where individuals in a crowd are tracked and holistic methods where the crowd is analyzed as a whole. In this work, the aim is to ...
Mean-Shift Tracking for Surveillance Applications Using Thermal and Visible Band Data Fusion
Beyan, Cigdem; Temizel, Alptekin (2011-04-28)
Separate tracking of objects such as people and the luggages they carry is important for video surveillance applications as it would allow making higher level inferences and timely detection of potential threats. However, this is a challenging problem and in the literature, people and objects they carry are tracked as a single object. In this study, we propose using thermal imagery in addition to the visible band imagery for tracking in indoor applications (such as airports, metro or railway stations). We u...
Citation Formats
A. E. Gündüz, T. Taşkaya Temizel, and A. Temizel, “Pedestrian zone anomaly detection by non-parametric temporal modelling,” 2014, Accessed: 00, 2020. [Online]. Available: