Semantic Analysis for Crowded Scenes Based on Non-Parametric Tracklet Clustering

@inproceedings{Hassanein2016SemanticAF,
  title={Semantic Analysis for Crowded Scenes Based on Non-Parametric Tracklet Clustering},
  author={Allam S. Hassanein and Mohamed E. Hussein and Walid Gomaa},
  booktitle={IJCAI},
  year={2016}
}
In this paper we address the problem of semantic analysis of structured/unstructured crowded video scenes. Our proposed approach relies on tracklets for motion representation. Each extracted tracklet is abstracted as a directed line segment, and a novel tracklet similarity measure is formulated based on line geometry. For analysis, we apply non-parametric clustering on the extracted tracklets. Particularly, we adapt the Distance Dependent Chinese Restaurant Process (DD-CRP) to leverage the… CONTINUE READING

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Gate and Common Pathway Detection in Crowd Scenes Using Motion Units and Meta-Tracking

  • 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
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Extracting descriptive motion information from crowd scenes

  • 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ)
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