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Sequential topic modeling for efficient analysis of traffic scenes

Ahmadi, P ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1109/ISTEL.2018.8661074
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2019
  4. Abstract:
  5. A two-level Sparse Topical Coding (STC) topic model is proposed in this paper for analyzing video sequences of traffic surveillance containing hierarchical patterns accompanied by complicated motions and co-occurrences. In order to automatically cluster optical flow features into motion patterns, a first level STC model is used. Next, the second level STC model is applied for clustering motion patterns into traffic phases. The effectiveness of the suggested method is proved by experiments on a traffic dataset in the real world. Our simulations show that the proposed two-level STC is able to extract the motion patterns and traffic phases accurately, leading to realistic describing the traffic videos. © 2018 IEEE
  6. Keywords:
  7. Temporal segmentation ; Topic model ; Anomaly detection ; Security systems ; Time and motion study ; Efficient analysis ; Hierarchical patterns ; Sequential topic models ; Sparse topical coding. (STC) ; Temporal segmentations ; Topic modeling ; Traffic phase ; Traffic surveillance ; Highway traffic control
  8. Source: 9th International Symposium on Telecommunication, IST 2018, 17 December 2018 through 19 December 2018 ; 2019 , Pages 559-564 ; 9781538682746 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/8661074