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A new method for traffic density estimation based on topic model

Kaviani, R ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/SPIS.2015.7422323
  3. Publisher: Institute of Electrical and Electronics Engineers Inc
  4. Abstract:
  5. Traffic density estimation plays an integral role in intelligent transportation systems (ITS), using which provides important information for signal control and effective traffic management. In this paper, we present a new framework for traffic density estimation based on topic model, which is an unsupervised model. This framework uses a set of visual features without any need to individual vehicle detection and tracking, and discovers the motion patterns automatically in traffic scenes by using topic model. Then, likelihood value allocated to each video clip enables us to estimate its traffic density. Results on a standard dataset show high classification performance of our proposed approach and robustness to typical environmental and illumination conditions
  6. Keywords:
  7. Intelligent transportation system ; Topic model ; Traffic density estimation ; Advanced traffic management systems ; Classification (of information) ; Highway traffic control ; Information management ; Intelligent systems ; Intelligent vehicle highway systems ; Signal processing ; Transportation ; Vehicle locating systems ; Classification performance ; Illumination conditions ; Signal control ; Topic Modeling ; Traffic densities ; Traffic management ; Vehicle detection ; Traffic signals
  8. Source: Signal Processing and Intelligent Systems Conference, 16 December 2015 through 17 December 2015 ; 2015 , Pages 114-118 ; 9781509001392 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/7422323