Location of Repository

Application of the self-organising map to trajectory classification

By Jonathan Owens and Andrew Hunter

Abstract

This paper presents an approach to the problem of automatically classifying events detected by video surveillance systems; specifically, of detecting unusual or suspicious movements. Approaches to this problem typically involve building complex 3D-models in real-world coordinates\ud to provide trajectory information for the classifier. In this paper we show that analysis of trajectories may be carried out in a model-free fashion, using self-organising\ud feature map neural networks to learn the characteristics of normal trajectories, and to detect novel ones. Trajectories are represented using positional and first and second order motion information, with moving-average smoothing. This allows novelty detection to be applied on a point-by-point basis in real time, and permits both instantaneous motion and whole trajectory motion to be subjected to novelty detection

Topics: G760 Machine Learning
Year: 2000
DOI identifier: 10.1109/VS.2000.856860
OAI identifier: oai:eprints.lincoln.ac.uk:1906

Suggested articles

Preview

Citations

  1. (1998). A Real-T ime System f or Vide o Surveillance of Unattended Outdoor Environments,” doi
  2. (1999). Adaptive Background Mixture Models for Real-Time Tracking,” doi
  3. (1998). Agent Orientated Annotation in Model Based Visual Surveillance,” doi
  4. (1997). An Integrated Traffic and Pedestrian Model-Based Vision System,”
  5. (1996). Comparison of Background Extraction Based Intrusion Detection Algorithms,” doi
  6. (1989). Illumination Independent Change Detection for Real World Sequences,” doi
  7. (1999). Improved Classification for a Data Fusing Kohonen SelfOrganising Map Using a Dynamic Thresholding Technique,”
  8. (1995). Learning the Distribution of Object Trajectories for Event Recognition,” doi
  9. (1995). Self-Organising Maps,” doi
  10. Using Adaptive Tracking to Classify and Monitor Activities in a Site,” doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.