Event Detection Based on a Pedestrian Interaction Graph Using Hidden Markov Models

  title={Event Detection Based on a Pedestrian Interaction Graph Using Hidden Markov Models},
  author={Florian Burkert and Matthias Butenuth},
In this paper, we present a new approach for event detection of pedestrian interaction in crowded and cluttered scenes. Existing work is focused on the detection of an abnormal event in general or on the detection of specific simple events incorporating only up to two trajectories. In our approach, event detection in large groups of pedestrians is performed by exploiting motion interaction between pairs of pedestrians in a graph-based framework. Event detection is done by analyzing the temporal… 
A new hierarchical event detection approach for highly complex scenarios in pedestrian groups on the basis of airborne image sequences from UAVs is presented by using a dynamic pedestrian graph of a scene which contains basic pairwise pedestrian motion interaction labels in the first layer.
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  • Computer Science
    2004 Conference on Computer Vision and Pattern Recognition Workshop
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An event detection framework that has two significant advantages over past work: an extended set of time-wise and object-wise statistical features including not only the trajectory coordinates but also the histograms and HMM based representations of object's speed, orientation, location, size, and aspect ratio and a spectral clustering algorithm that can automatically estimate the optimal number of clusters.
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Abnormal crowd behavior detection using social force model
A novel method to detect and localize abnormal behaviors in crowd videos using Social Force model and it is shown that the social force approach outperforms similar approaches based on pure optical flow.
Robust Real-Time Unusual Event Detection using Multiple Fixed-Location Monitors
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The proposed method provides a new higher-level layer to the traditional surveillance pipeline for anomalous event detection and scene model feedback and successfully used the proposed scene model to detect local as well as global anomalies in object tracks.
A system for learning statistical motion patterns
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  • Physics
    Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
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Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.
People trajectory mining with statistical pattern recognition
  • S. Calderara, R. Cucchiara
  • Computer Science
    2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops
  • 2010
A statistical framework for trajectories mining that analyzes, in an integrated solution, several aspects of the trajectories such as location, shape and speed properties and demonstrates the efficacy of the framework in clustering people trajectories with the purpose of analyze frequent behaviors in complex environments.