Visual Analysis of Extremely Dense Crowded Scenes

Visual Analysis of Extremely Dense Crowded Scenes

UCF CRCV via YouTube Direct link

Framework

25 of 46

25 of 46

Framework

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Classroom Contents

Visual Analysis of Extremely Dense Crowded Scenes

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  1. 1 Motivation
  2. 2 Presentation Layout
  3. 3 Key Ideas
  4. 4 Problems
  5. 5 Related Work: Counting by Detection
  6. 6 Related Work: Counting by Regression
  7. 7 Spatial Poisson Counting Process
  8. 8 Patches: Head Detections
  9. 9 Patches: Fourier Analysis
  10. 10 Patches: Interest Points
  11. 11 Patches: Fusion
  12. 12 Images: Multi-scale MRF
  13. 13 Results: Quantitative
  14. 14 Results: Per Patch Analysis
  15. 15 Results: Performance Analysis
  16. 16 Results: Analysis of 10th Group
  17. 17 Localization
  18. 18 Schematic Outline
  19. 19 Search results: Uniform Grid
  20. 20 Finding Representative Templates
  21. 21 Hypotheses Selection
  22. 22 Optimization
  23. 23 Bint Quadratic Programming
  24. 24 Background: Deformable Parts Model
  25. 25 Framework
  26. 26 Scale and Confidence Priors
  27. 27 Intermediate Results
  28. 28 Combination-of-Parts (COP) Detection
  29. 29 Global Occlusion Reasoning
  30. 30 Dataset: UCF-HDDC
  31. 31 Results: Qualitative
  32. 32 Results: Step-wise Improvement
  33. 33 Results: Density based Analysis
  34. 34 Results: Comparison
  35. 35 Results: Failure Cases
  36. 36 Chapter Summary
  37. 37 Queen Detection
  38. 38 Detection of Prominent Individuals
  39. 39 Modeling Crowd Behavior
  40. 40 Neighborhood Motion Concurrence
  41. 41 Tracking: Hierarchical Update
  42. 42 Experiments: Sequences
  43. 43 Quantitative Comparison
  44. 44 Component Contribution
  45. 45 Dissertation Conclusion
  46. 46 Future Work

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