Robust vehicle tracking for urban traffic videos at intersections

C. Li, A. Chiang, G. Dobler, Y. Wang, K. Xie, K. Ozbay, M. Ghandehari, J. Zhou, D. Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We develop a robust, unsupervised vehicle tracking system for videos of very congested road intersections in urban environments. Raw tracklets from the standard Kanade-Lucas-Tomasi tracking algorithm are treated as sample points and grouped to form different vehicle candidates. Each tracklet is described by multiple features including position, velocity, and a foreground score derived from robust PCA background subtraction. By considering each tracklet as a node in a graph, we build the adjacency matrix for the graph based on the feature similarity between the tracklets and group these tracklets using spectral embedding and Dirichelet Process Gaussian Mixture Models. The proposed system yields excellent performance for traffic videos captured in urban environments and highways.

Original languageEnglish (US)
Title of host publication2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages207-213
Number of pages7
ISBN (Electronic)9781509038114
DOIs
StatePublished - Nov 7 2016
Event13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016 - Colorado Springs, United States
Duration: Aug 23 2016Aug 26 2016

Publication series

Name2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016

Other

Other13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016
CountryUnited States
CityColorado Springs
Period8/23/168/26/16

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Instrumentation
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Robust vehicle tracking for urban traffic videos at intersections'. Together they form a unique fingerprint.

  • Cite this

    Li, C., Chiang, A., Dobler, G., Wang, Y., Xie, K., Ozbay, K., Ghandehari, M., Zhou, J., & Wang, D. (2016). Robust vehicle tracking for urban traffic videos at intersections. In 2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016 (pp. 207-213). [7738075] (2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AVSS.2016.7738075