Video Traffic Analysis for Abnormal Event Detection

Details

• Creators:
  Katsaggelos, A.K. ; Tsaftaris, S. ; Wu, Y.
• Corporate Creators:
  Northwestern University (Evanston, Ill.). Dept. of Electrical Engineering and Computer Science
• Subject/TRT Terms:
  • Traffic surveillance
  • Traffic congestion
  • Digital video
  • Video cameras
  • Image processing
  • Traffic monitoring
  • Image processing--Digital techniques
  • Digital video
  • Traffic congestion--Management
• Resource Type:
  Tech Report
• Geographical Coverage:
  Illinois
• Edition:
  Final report.
• Corporate Publisher:
  Northwestern University (Evanston, Ill.). Center for the Commercialization of Innovative Transportation Technology
• Abstract:
  We propose the use of video imaging sensors for the detection and classification of abnormal events to ; be used primarily for mitigation of traffic congestion. Successful detection of such events will allow for ; new road guidelines; for rapid deployment of various transportation and safety agencies; for interactive ; displays that alert drivers to, for example, slow down or speed up, move to a different lane, or, alter ; their driving behavior, so as to reduce the probability of traffic congestion or the occurrence of more ; abnormal events. Deciding on additional road guidelines or proper display information, can be ; accomplished either via computer simulations or experimentation with field implementations. We ; extended in‐house developed algorithms to detect and track vehicles in video sequences and analyze ; their trajectories. Through analysis we will classify their trajectories independently but also considering ; vehicle interactions, into abnormal and normal events. A main objective of the analysis is to determine ; how each type of abnormal event affects subsequent traffic, and serves as a predictor of congestion ; build up. Towards this task we will identify each type of abnormal event by implementing a supervised ; classifier, and built models to describe them and their effect (over time).
  More +
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/18088/dot_18088_DS1.pdf
• File Type:
  [PDF - 4.74 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha256:cd6ec40fd6324339599c573f37a54405c46990a157c642bb8a5ce0fa16e34601